@misc{Sagnol, author = {Sagnol, Guillaume}, title = {Approximation of a Maximum-Submodular-Coverage problem involving spectral functions, with application to Experimental Design}, volume = {151}, number = {1--2}, issn = {1438-0064}, doi = {10.1016/j.dam.2012.07.016}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14956}, pages = {258 -- 276}, abstract = {We study a family of combinatorial optimization problems defined by a parameter \$p\in[0,1]\$, which involves spectral functions applied to positive semidefinite matrices, and has some application in the theory of optimal experimental design. This family of problems tends to a generalization of the classical maximum coverage problem as \$p\$ goes to \$0\$, and to a trivial instance of the knapsack problem as \$p\$ goes to \$1\$. In this article, we establish a matrix inequality which shows that the objective function is submodular for all \$p\in[0,1]\$, from which it follows that the greedy approach, which has often been used for this problem, always gives a design within \$1-1/e\$ of the optimum. We next study the design found by rounding the solution of the continuous relaxed problem, an approach which has been applied by several authors. We prove an inequality which generalizes a classical result from the theory of optimal designs, and allows us to give a rounding procedure with an approximation factor which tends to \$1\$ as \$p\$ goes to \$1\$.}, language = {en} } @misc{BorndoerferOmontSagnoletal., author = {Bornd{\"o}rfer, Ralf and Omont, Bertrand and Sagnol, Guillaume and Swarat, Elmar}, title = {A Stackelberg game to optimize the distribution of controls in transportation networks}, issn = {1438-0064}, doi = {10.1007/978-3-642-35582-0_17}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14995}, abstract = {We propose a game theoretic model for the spatial distribution of inspectors on a transportation network. The problem is to spread out the controls so as to enforce the payment of a transit toll. We formulate a linear program to find the control distribution which maximizes the expected toll revenue, and a mixed integer program for the problem of minimizing the number of evaders. Furthermore, we show that the problem of finding an optimal mixed strategy for a coalition of \$N\$ inspectors can be solved efficiently by a column generation procedure. Finally, we give experimental results from an application to the truck toll on German motorways.}, language = {en} } @misc{BorndoerferSagnolSwarat, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Swarat, Elmar}, title = {An IP Approach to Toll Enforcement Optimization on German Motorways}, issn = {1438-0064}, doi = {10.1007/978-3-642-29210-1_51}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14299}, number = {11-42}, abstract = {This paper proposes the first model for toll enforcement optimization on German motorways. The enforcement is done by mobile control teams and our goal is to produce a schedule achieving network-wide control, proportional to spatial and time-dependent traffic distributions. Our model consists of two parts. The first plans control tours using a vehicle routing approach with profits and some side constraints. The second plans feasible rosters for the control teams. Both problems can be modeled as Multi-Commodity Flow Problems. Adding additional coupling constraints produces a large-scale integrated integer programming formulation. We show that this model can be solved to optimality for real world instances associated with a control area in East Germany.}, language = {en} } @misc{Sagnol, author = {Sagnol, Guillaume}, title = {Network-related problems in Optimal Experimental Design and Second Order Cone Programming}, volume = {51}, number = {51}, issn = {1438-0064}, doi = {10.2478/v10127-012-0016-x}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14942}, pages = {161 -- 171}, abstract = {In the past few years several applications of optimal experimental designs have emerged to optimize the measurements in communication networks. The optimal design problems arising from this kind of applications share three interesting properties: (i) measurements are only available at a small number of locations of the network; (ii) each monitor can simultaneously measure several quantities, which can be modeled by ``multiresponse experiments"; (iii) the observation matrices depend on the topology of the network. In this paper, we give an overview of these experimental design problems and recall recent results for the computation of optimal designs by Second Order Cone Programming (SOCP). New results for the network-monitoring of a discrete time process are presented. In particular, we show that the optimal design problem for the monitoring of an AR1 process can be reduced to the standard form and we give experimental results.}, language = {en} } @misc{SagnolBlancoSauvage, author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibaut}, title = {The Cone of Flow Matrices: Approximation Hierarchies and Applications}, issn = {1438-0064}, doi = {10.1002/net.21820}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-64399}, abstract = {Let G be a directed acyclic graph with n arcs, a source s and a sink t. We introduce the cone K of flow matrices, which is a polyhedral cone generated by the matrices \$\vec{1}_P\vec{1}_P^T\in\RR^{n\times n}\$, where \$\vec{1}_P\in\RR^n\$ is the incidence vector of the (s,t)-path P. We show that several hard flow (or path) optimization problems, that cannot be solved by using the standard arc-representation of a flow, reduce to a linear optimization problem over \$\mathcal{K}\$. This cone is intractable: we prove that the membership problem associated to \$\mathcal{K}\$ is NP-complete. However, the affine hull of this cone admits a nice description, and we give an algorithm which computes in polynomial-time the decomposition of a matrix \$X\in \operatorname{span} \mathcal{K}\$ as a linear combination of some \$\vec{1}_P\vec{1}_P^T\$'s. Then, we provide two convergent approximation hierarchies, one of them based on a completely positive representation of~K. We illustrate this approach by computing bounds for the quadratic shortest path problem, as well as a maximum flow problem with pairwise arc-capacities.}, language = {en} } @misc{BorndoerferBuwayaSagnoletal., author = {Bornd{\"o}rfer, Ralf and Buwaya, Julia and Sagnol, Guillaume and Swarat, Elmar}, title = {Network Spot Checking Games: Theory and Application to Toll Enforcing in Transportation Networks}, issn = {1438-0064}, doi = {10.1002/net.21596}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-47139}, abstract = {We introduce the class of spot-checking games (SC games). These games model problems where the goal is to distribute fare inspectors over a toll network. In an SC game, the pure strategies of network users correspond to paths in a graph, and the pure strategies of the inspectors are subset of edges to be controlled. Although SC games are not zero-sum, we show that a Nash equilibrium can be computed by linear programming. The computation of a strong Stackelberg equilibrium is more relevant for this problem, but we show that this is NP-hard. However, we give some bounds on the \emph{price of spite}, which measures how the payoff of the inspector degrades when committing to a Nash equilibrium. Finally, we demonstrate the quality of these bounds for a real-world application, namely the enforcement of a truck toll on German motorways.}, language = {en} } @article{Sagnol, author = {Sagnol, Guillaume}, title = {On the semidefinite representation of real functions applied to symmetric matrices}, series = {Linear Algebra and its Applications}, volume = {439}, journal = {Linear Algebra and its Applications}, number = {10}, doi = {10.1016/j.laa.2013.08.021}, pages = {2829 -- 2843}, abstract = {We present a new semidefinite representation for the trace of a real function f applied to symmetric matrices, when a semidefinite representation of the convex function f is known. Our construction is intuitive, and yields a representation that is more compact than the previously known one. We also show with the help of matrix geometric means and the Riemannian metric of the set of positive definite matrices that for a rational number p in the interval (0,1], the matrix X raised to the exponent p is the largest element of a set represented by linear matrix inequalities. We give numerical results for a problem inspired from the theory of experimental designs, which show that the new semidefinite programming formulation yields a speed-up factor in the order of 10.}, language = {en} } @article{Sagnol, author = {Sagnol, Guillaume}, title = {Approximation of a maximum-submodular-coverage problem involving spectral functions, with application to experimental designs}, series = {Discrete Applied Mathematics}, volume = {161}, journal = {Discrete Applied Mathematics}, number = {1-2}, doi = {10.1016/j.dam.2012.07.016}, pages = {258 -- 276}, abstract = {We study a family of combinatorial optimization problems defined by a parameter \$p\in[0,1]\$, which involves spectral functions applied to positive semidefinite matrices, and has some application in the theory of optimal experimental design. This family of problems tends to a generalization of the classical maximum coverage problem as \$p\$ goes to \$0\$, and to a trivial instance of the knapsack problem as \$p\$ goes to \$1\$. In this article, we establish a matrix inequality which shows that the objective function is submodular for all \$p\in[0,1]\$, from which it follows that the greedy approach, which has often been used for this problem, always gives a design within \$1-1/e\$ of the optimum. We next study the design found by rounding the solution of the continuous relaxed problem, an approach which has been applied by several authors. We prove an inequality which generalizes a classical result from the theory of optimal designs, and allows us to give a rounding procedure with an approximation factor which tends to \$1\$ as \$p\$ goes to \$1\$.}, language = {en} } @inproceedings{Sagnol, author = {Sagnol, Guillaume}, title = {Network-related problems in optimal experimental design and second order cone programming}, series = {Proceedings of PROBASTAT'2011, Tatra Mountains Mathematical Publications}, volume = {51}, booktitle = {Proceedings of PROBASTAT'2011, Tatra Mountains Mathematical Publications}, doi = {10.2478/v10127-012-0016-x}, pages = {161 -- 171}, abstract = {In the past few years several applications of optimal experimental designs have emerged to optimize the measurements in communication networks. The optimal design problems arising from this kind of applications share three interesting properties: (i) measurements are only available at a small number of locations of the network; (ii) each monitor can simultaneously measure several quantities, which can be modeled by ``multiresponse experiments"; (iii) the observation matrices depend on the topology of the network. In this paper, we give an overview of these experimental design problems and recall recent results for the computation of optimal designs by Second Order Cone Programming (SOCP). New results for the network-monitoring of a discrete time process are presented. In particular, we show that the optimal design problem for the monitoring of an AR1 process can be reduced to the standard form and we give experimental results.}, language = {en} } @article{Sagnol, author = {Sagnol, Guillaume}, title = {A class of Semidefinite Programs with rank-one solutions}, series = {Linear Algebra and its Applications}, volume = {435}, journal = {Linear Algebra and its Applications}, number = {6}, doi = {10.1016/j.laa.2011.03.027}, pages = {1446 -- 1463}, abstract = {We show that a class of semidefinite programs (SDP) admits a solution that is a positive semidefinite matrix of rank at most \$r\$, where \$r\$ is the rank of the matrix involved in the objective function of the SDP. The optimization problems of this class are semidefinite packing problems, which are the SDP analogs to vector packing problems. Of particular interest is the case in which our result guarantees the existence of a solution of rank one: we show that the computation of this solution actually reduces to a Second Order Cone Program (SOCP). We point out an application in statistics, in the optimal design of experiments.}, language = {en} } @inproceedings{BorndoerferBuwayaSagnoletal., author = {Bornd{\"o}rfer, Ralf and Buwaya, Julia and Sagnol, Guillaume and Swarat, Elmar}, title = {Optimizing Toll Enforcement in Transportation Networks: a Game-Theoretic Approach}, series = {Proceedings of INOC'2013}, volume = {41}, booktitle = {Proceedings of INOC'2013}, doi = {http://dx.doi.org//10.1016/j.endm.2013.05.100}, pages = {253 -- 260}, abstract = {We present a game-theoretic approach to optimize the strategies of toll enforcement on a motorway network. In contrast to previous approaches, we consider a network with an arbitrary topology, and we handle the fact that users may choose their Origin-Destination path; in particular they may take a detour to avoid sections with a high control rate. We show that a Nash equilibrium can be computed with an LP (although the game is not zero-sum), and we give a MIP for the computation of a Stackelberg equilibrium. Experimental results based on an application to the enforcement of a truck toll on German motorways are presented.}, language = {en} } @inproceedings{BorndoerferOmontSagnoletal., author = {Bornd{\"o}rfer, Ralf and Omont, Bertrand and Sagnol, Guillaume and Swarat, Elmar}, title = {A Stackelberg game to optimize the distribution of controls in transportation networks}, series = {Proceedings of the 3rd International Conference on Game Theory for Networks (GAMENETS 2012)}, volume = {105}, booktitle = {Proceedings of the 3rd International Conference on Game Theory for Networks (GAMENETS 2012)}, doi = {http://dx.doi.org/10.1007/978-3-642-35582-0_17}, pages = {224 -- 235}, abstract = {We propose a game theoretic model for the spatial distribution of inspectors on a transportation network. The problem is to spread out the controls so as to enforce the payment of a transit toll. We formulate a linear program to find the control distribution which maximizes the expected toll revenue, and a mixed integer program for the problem of minimizing the number of evaders. Furthermore, we show that the problem of finding an optimal mixed strategy for a coalition of \$N\$ inspectors can be solved efficiently by a column generation procedure. Finally, we give experimental results from an application to the truck toll on German motorways.}, language = {en} } @article{BorndoerferSagnolSchlechteetal., author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Schlechte, Thomas and Swarat, Elmar}, title = {Optimal duty rostering for toll enforcement inspectors}, series = {Annals of Operations Research}, volume = {252(2)}, journal = {Annals of Operations Research}, edition = {252}, publisher = {Springer US}, doi = {10.1007/s10479-016-2152-1}, pages = {383 -- 406}, abstract = {We present the problem of planning mobile tours of inspectors on German motorways to enforce the payment of the toll for heavy good trucks. This is a special type of vehicle routing problem with the objective to conduct as good inspections as possible on the complete network. In addition, we developed a personalized crew rostering model, to schedule the crews of the tours. The planning of daily tours and the rostering are combined in a novel integrated approach and formulated as a complex and large scale Integer Program. The main focus of this paper extends our previous publications on how different requirements for the rostering can be modeled in detail. The second focus is on a bi-criteria analysis of the planning problem to find the balance between the control quality and the roster acceptance. Finally, computational results on real-world instances show the practicability of our method and how different input parameters influence the problem complexity.}, language = {en} } @inproceedings{SagnolHegeWeiser, author = {Sagnol, Guillaume and Hege, Hans-Christian and Weiser, Martin}, title = {Using sparse kernels to design computer experiments with tunable precision}, series = {22nd Intern. Conf. on Computational Statistics - COMPSTAT 2016, Oviedo, Spain, 23-26 August 2016, Proceedings ISBN 978-90-73592-36-0}, booktitle = {22nd Intern. Conf. on Computational Statistics - COMPSTAT 2016, Oviedo, Spain, 23-26 August 2016, Proceedings ISBN 978-90-73592-36-0}, pages = {397 -- 408}, language = {en} } @inproceedings{BorndoerferSagnolSwarat, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Swarat, Elmar}, title = {An IP Approach to Toll Enforcement Optimization on German Motorways}, series = {Operations Research Proceedings 2011}, booktitle = {Operations Research Proceedings 2011}, doi = {10.1007/978-3-642-29210-1_51}, pages = {317 -- 322}, abstract = {This paper proposes the first model for toll enforcement optimization on German motorways. The enforcement is done by mobile control teams and our goal is to produce a schedule achieving network-wide control, proportional to spatial and time-dependent traffic distributions. Our model consists of two parts. The first plans control tours using a vehicle routing approach with profits and some side constraints. The second plans feasible rosters for the control teams. Both problems can be modeled as Multi-Commodity Flow Problems. Adding additional coupling constraints produces a large-scale integrated integer programming formulation. We show that this model can be solved to optimality for real world instances associated with a control area in East Germany.}, language = {en} } @inproceedings{BorndoerferSagnolSwarat, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Swarat, Elmar}, title = {A Case Study on Optimizing Toll Enforcements on Motorways}, series = {3rd Student Conference on Operational Research}, volume = {22}, booktitle = {3rd Student Conference on Operational Research}, doi = {10.4230/OASIcs.SCOR.2012.1}, pages = {1 -- 10}, abstract = {In this paper we present the problem of computing optimal tours of toll inspectors on German motorways. This problem is a special type of vehicle routing problem and builds up an integrated model, consisting of a tour planning and a duty rostering part. The tours should guarantee a network-wide control whose intensity is proportional to given spatial and time dependent traffic distributions. We model this using a space-time network and formulate the associated optimization problem by an integer program (IP). Since sequential approaches fail, we integrated the assignment of crews to the tours in our model. In this process all duties of a crew member must fit in a feasible roster. It is modeled as a Multi-Commodity Flow Problem in a directed acyclic graph, where specific paths correspond to feasible rosters for one month. We present computational results in a case-study on a German subnetwork which documents the practicability of our approach.}, language = {en} } @misc{DuarteSagnolWong, author = {Duarte, Belmiro P.M. and Sagnol, Guillaume and Wong, Weng Kee}, title = {An algorithm based on Semidefinite Programming for finding minimax optimal designs}, issn = {1438-0064}, doi = {10.1016/j.csda.2017.09.008}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-66249}, abstract = {An algorithm based on a delayed constraint generation method for solving semi-infinite programs for constructing minimax optimal designs for nonlinear models is proposed. The outer optimization level of the minimax optimization problem is solved using a semidefinite programming based approach that requires the design space be discretized. A nonlinear programming solver is then used to solve the inner program to determine the combination of the parameters that yields the worst-case value of the design criterion. The proposed algorithm is applied to find minimax optimal designs for the logistic model, the flexible 4-parameter Hill homoscedastic model and the general nth order consecutive reaction model, and shows that it (i) produces designs that compare well with minimax \$D-\$optimal designs obtained from semi-infinite programming method in the literature; (ii) can be applied to semidefinite representable optimality criteria, that include the common A-, E-,G-, I- and D-optimality criteria; (iii) can tackle design problems with arbitrary linear constraints on the weights; and (iv) is fast and relatively easy to use.}, language = {en} } @misc{DuarteSagnol, author = {Duarte, Belmiro P.M. and Sagnol, Guillaume}, title = {Approximate and exact D-optimal designs for \$2^k\$ factorial experiments for Generalized Linear Models via SOCP}, issn = {1438-0064}, doi = {10.1007/s00362-018-01075-7}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-66256}, abstract = {We propose (Mixed Integer) Second Order Cone Programming formulations to find approximate and exact \$D-\$optimal designs for \$2^k\$ factorial experiments for Generalized Linear Models (GLMs). Locally optimal designs are addressed with Second Order Cone Programming (SOCP) and Mixed Integer Second Order Cone Programming (MISOCP) formulations. The formulations are extended for scenarios of parametric uncertainty employing the Bayesian framework for \emph{log det} \$D-\$optimality criterion. A quasi Monte-Carlo sampling procedure based on the Hammersley sequence is used for integrating the optimality criterion in the parametric region. The problems are solved in \texttt{GAMS} environment using \texttt{CPLEX} solver. We demonstrate the application of the algorithm with the logistic, probit and complementary log-log models and consider full and fractional factorial designs.}, language = {en} } @article{DuarteSagnolWong, author = {Duarte, Belmiro P.M. and Sagnol, Guillaume and Wong, Weng Kee}, title = {An algorithm based on Semidefinite Programming for finding minimax optimal designs}, series = {Computational Statistics \& Data Analysis}, volume = {119}, journal = {Computational Statistics \& Data Analysis}, doi = {10.1016/j.csda.2017.09.008}, pages = {99 -- 117}, language = {en} } @misc{SagnolHarman, author = {Sagnol, Guillaume and Harman, Radoslav}, title = {Computing exact D-optimal designs by mixed integer second order cone programming}, issn = {1438-0064}, doi = {10.1214/15-AOS1339}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-41932}, abstract = {Let the design of an experiment be represented by an \$s\$-dimensional vector \$\vec{w}\$ of weights with non-negative components. Let the quality of \$\vec{w}\$ for the estimation of the parameters of the statistical model be measured by the criterion of \$D\$-optimality defined as the \$m\$-th root of the determinant of the information matrix \$M(\vec{w})=\sum_{i=1}^s w_iA_iA_i^T\$, where \$A_i\$, \$i=1,...,s\$, are known matrices with \$m\$ rows. In the paper, we show that the criterion of \$D\$-optimality is second-order cone representable. As a result, the method of second order cone programming can be used to compute an approximate \$D\$-optimal design with any system of linear constraints on the vector of weights. More importantly, the proposed characterization allows us to compute an \emph{exact} \$D\$-optimal design, which is possible thanks to high-quality branch-and-cut solvers specialized to solve mixed integer second order cone problems. We prove that some other widely used criteria are also second order cone representable, for instance the criteria of \$A\$-, and \$G\$-optimality, as well as the criteria of \$D_K\$- and \$A_K\$-optimality, which are extensions of \$D\$-, and \$A\$-optimality used in the case when only a specific system of linear combinations of parameters is of interest. We present several numerical examples demonstrating the efficiency and universality of the proposed method. We show that in many cases the mixed integer second order cone programming approach allows us to find a provably optimal exact design, while the standard heuristics systematically miss the optimum.}, language = {en} } @misc{SagnolBalzerBorndoerferetal., author = {Sagnol, Guillaume and Balzer, Felix and Bornd{\"o}rfer, Ralf and Spies, Claudia and von Dincklage, Falk}, title = {Makespan and Tardiness in Activity Networks with Lognormal Activity Durations}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-59290}, abstract = {We propose an algorithm to approximate the distribution of the completion time (makespan) and the tardiness costs of a project, when durations are lognormally distributed. This problem arises naturally for the optimization of surgery scheduling, where it is very common to assume lognormal procedure times. We present an analogous of Clark's formulas to compute the moments of the maximum of a set of lognormal variables. Then, we use moment matching formulas to approximate the earliest starting time of each activity of the project by a shifted lognormal variable. This approach can be seen as a lognormal variant of a state-of-the-art method used for the statistical static timing analysis (SSTA) of digital circuits. We carried out numerical experiments with instances based on real data from the application to surgery scheduling. We obtained very promising results, especially for the approximation of the mean overtime in operating rooms, for which our algorithm yields results of a similar quality to Monte-Carlo simulations requiring an amount of computing time several orders of magnitude larger.}, language = {en} } @inproceedings{BorndoerferSagnolSchwartz, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Schwartz, Stephan}, title = {An Extended Network Interdiction Problem for Optimal Toll Control}, series = {INOC 2015 - 7th International Network Optimization Conference}, volume = {52}, booktitle = {INOC 2015 - 7th International Network Optimization Conference}, doi = {10.1016/j.endm.2016.03.040}, pages = {301 -- 308}, abstract = {We study an extension of the shortest path network interdiction problem and present a novel real-world application in this area. We consider the problem of determining optimal locations for toll control stations on the arcs of a transportation network. We handle the fact that drivers can avoid control stations on parallel secondary roads. The problem is formulated as a mixed integer program and solved using Benders decomposition. We present experimental results for the application of our models to German motorways.}, language = {en} } @misc{SagnolHegeWeiser, author = {Sagnol, Guillaume and Hege, Hans-Christian and Weiser, Martin}, title = {Using sparse kernels to design computer experiments with tunable precision}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-59605}, abstract = {Statistical methods to design computer experiments usually rely on a Gaussian process (GP) surrogate model, and typically aim at selecting design points (combinations of algorithmic and model parameters) that minimize the average prediction variance, or maximize the prediction accuracy for the hyperparameters of the GP surrogate. In many applications, experiments have a tunable precision, in the sense that one software parameter controls the tradeoff between accuracy and computing time (e.g., mesh size in FEM simulations or number of Monte-Carlo samples). We formulate the problem of allocating a budget of computing time over a finite set of candidate points for the goals mentioned above. This is a continuous optimization problem, which is moreover convex whenever the tradeoff function accuracy vs. computing time is concave. On the other hand, using non-concave weight functions can help to identify sparse designs. In addition, using sparse kernel approximations drastically reduce the cost per iteration of the multiplicative weights updates that can be used to solve this problem.}, language = {en} } @inproceedings{DuarteSagnolOliveira, author = {Duarte, Belmiro P.M. and Sagnol, Guillaume and Oliveira, Nuno M.C.}, title = {A Robust Minimax Semidefinite Programming Formulation for Optimal Design of Experiments for Model Parametrization}, series = {12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering}, volume = {37}, booktitle = {12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering}, doi = {10.1016/B978-0-444-63578-5.50146-8}, pages = {905 -- 910}, abstract = {Model-based optimal design of experiments (M-bODE) is a crucial step in model parametrization since it encloses a framework that maximizes the amount of information extracted from a battery of lab experiments. We address the design of M-bODE for dynamic models considering a continuous representation of the design. We use Semidefinite Programming (SDP) to derive robust minmax formulations for nonlinear models, and extend the formulations to other criteria. The approaches are demonstrated for a CSTR where a two-step reaction occurs.}, language = {en} } @article{SagnolHarman, author = {Sagnol, Guillaume and Harman, Radoslav}, title = {Computing exact D-optimal designs by mixed integer second-order cone programming}, series = {The Annals of Statistics}, volume = {43}, journal = {The Annals of Statistics}, number = {5}, doi = {10.1214/15-AOS1339}, pages = {2198 -- 2224}, abstract = {Let the design of an experiment be represented by an \$s-\$dimensional vector \$w\$ of weights with nonnegative components. Let the quality of \$w\$ for the estimation of the parameters of the statistical model be measured by the criterion of \$D-\$optimality, defined as the \$m\$th root of the determinant of the information matrix \$M(w)=\sum_{i=1}^s w_i A_i A_i^T\$, where \$A_i\$,\$i=1,\ldots,s\$ are known matrices with \$m\$ rows. In this paper, we show that the criterion of \$D-\$optimality is second-order cone representable. As a result, the method of second-order cone programming can be used to compute an approximate \$D-\$optimal design with any system of linear constraints on the vector of weights. More importantly, the proposed characterization allows us to compute an exact \$D-\$optimal design, which is possible thanks to high-quality branch-and-cut solvers specialized to solve mixed integer second-order cone programming problems. Our results extend to the case of the criterion of \$D_K-\$optimality, which measures the quality of \$w\$ for the estimation of a linear parameter subsystem defined by a full-rank coefficient matrix \$K\$. We prove that some other widely used criteria are also second-order cone representable, for instance, the criteria of \$A-\$, \$A_K\$-, \$G-\$ and \$I-\$optimality. We present several numerical examples demonstrating the efficiency and general applicability of the proposed method. We show that in many cases the mixed integer second-order cone programming approach allows us to find a provably optimal exact design, while the standard heuristics systematically miss the optimum.}, language = {en} } @misc{SagnolBorndoerferGrimaetal., author = {Sagnol, Guillaume and Bornd{\"o}rfer, Ralf and Grima, Micka{\"e}l and Seeling, Matthes and Spies, Claudia}, title = {Robust Allocation of Operating Rooms with Lognormal case Durations}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-58497}, abstract = {The problem of allocating operating rooms (OR) to surgical cases is a challenging task, involving both combinatorial aspects and uncertainty handling. In this article, we formulate this problem as a job shop scheduling problem, in which the job durations follow a lognormal distribution. We propose to use a cutting-plane approach to solve a robust version of this optimization problem. To this end, we develop an algorithm based on fixed-point iterations to solve the subproblems that identify worst-case scenarios and generate cut inequalities. The procedure is illustrated with numerical experiments based on real data from a major hospital in Berlin.}, language = {en} } @misc{SagnolBarnerBorndoerferetal., author = {Sagnol, Guillaume and Barner, Christoph and Bornd{\"o}rfer, Ralf and Grima, Micka{\"e}l and Seeling, Matthes and Spies, Claudia and Wernecke, Klaus}, title = {Robust Allocation of Operating Rooms: a Cutting Plane Approach to handle Lognormal Case Durations}, issn = {1438-0064}, doi = {10.1016/j.ejor.2018.05.022}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-58502}, abstract = {The problem of allocating operating rooms (OR) to surgical cases is a challenging task, involving both combinatorial aspects and uncertainty handling. We formulate this problem as a parallel machines scheduling problem, in which job durations follow a lognormal distribution, and a fixed assignment of jobs to machines must be computed. We propose a cutting-plane approach to solve the robust counterpart of this optimization problem. To this end, we develop an algorithm based on fixed-point iterations that identifies worst-case scenarios and generates cut inequalities. The main result of this article uses Hilbert's projective geometry to prove the convergence of this procedure under mild conditions. We also propose two exact solution methods for a similar problem, but with a polyhedral uncertainty set, for which only approximation approaches were known. Our model can be extended to balance the load over several planning periods in a rolling horizon. We present extensive numerical experiments for instances based on real data from a major hospital in Berlin. In particular, we find that: (i) our approach performs well compared to a previous model that ignored the distribution of case durations; (ii) compared to an alternative stochastic programming approach, robust optimization yields solutions that are more robust against uncertainty, at a small price in terms of average cost; (iii) the \emph{longest expected processing time first} (LEPT) heuristic performs well and efficiently protects against extreme scenarios, but only if a good prediction model for the durations is available. Finally, we draw a number of managerial implications from these observations.}, language = {en} } @misc{BorndoerferSagnolSchlechteetal., author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Schlechte, Thomas and Swarat, Elmar}, title = {Optimal Toll Enforcement - an Integration of Vehicle Routing and Duty Rostering}, issn = {1438-0064}, doi = {10.1007/s10479-016-2152-1}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-45107}, abstract = {We present the problem of planning mobile tours of inspectors on German motorways to enforce the payment of the toll for heavy good trucks. This is a special type of vehicle routing problem with the objective to conduct as good inspections as possible on the complete network. In addition, the crews of the tours have to be scheduled. Thus, we developed a personalized crew rostering model. The planning of daily tours and the rostering are combined in a novel integrated approach and formulated as a complex and large scale Integer Program. The paper focuses first on different requirements for the rostering and how they can be modeled in detail. The second focus is on a bicriterion analysis of the planning problem to find the balance between the control quality and the roster acceptance. On the one hand the tour planning is a profit maximization problem and on the other hand the rostering should be made in a employee friendly way. Finally, computational results on real-world instances show the practicability of our method.}, language = {en} } @inproceedings{SagnolBorndoerferSchlechteetal., author = {Sagnol, Guillaume and Bornd{\"o}rfer, Ralf and Schlechte, Thomas and Swarat, Elmar}, title = {The Price of Spite in Spot-checking games}, series = {7th International Symposium on Algorithmic Game Theory (SAGT'2014)}, volume = {8768}, booktitle = {7th International Symposium on Algorithmic Game Theory (SAGT'2014)}, editor = {Lavi, Ron}, publisher = {Springer}, isbn = {978-3-662-44802-1}, doi = {10.1007/978-3-662-44803-8}, pages = {293}, abstract = {We introduce the class of spot-checking games (SC games). These games model problems where the goal is to distribute fare inspectors over a toll network. Although SC games are not zero-sum, we show that a Nash equilibrium can be computed by linear programming. The computation of a strong Stackelberg equilibrium is more relevant for this problem, but we show that this is NP-hard. However, we give some bounds on the \emph{price of spite}, which measures how the payoff of the inspector degrades when committing to a Nash equilibrium. Finally, we demonstrate the quality of these bounds for a real-world application, namely the enforcement of a truck toll on German motorways.}, language = {en} } @misc{SagnolBorndoerferSchlechteetal., author = {Sagnol, Guillaume and Bornd{\"o}rfer, Ralf and Schlechte, Thomas and Swarat, Elmar}, title = {The Price of Spite in Spot-checking games}, issn = {1438-0064}, doi = {10.1007/978-3-662-44803-8}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52775}, abstract = {We introduce the class of spot-checking games (SC games). These games model problems where the goal is to distribute fare inspectors over a toll network. Although SC games are not zero-sum, we show that a Nash equilibrium can be computed by linear programming. The computation of a strong Stackelberg equilibrium is more relevant for this problem, but we show that this is NP-hard. However, we give some bounds on the \emph{price of spite}, which measures how the payoff of the inspector degrades when committing to a Nash equilibrium. Finally, we demonstrate the quality of these bounds for a real-world application, namely the enforcement of a truck toll on German motorways.}, language = {en} } @misc{SagnolHarman, author = {Sagnol, Guillaume and Harman, Radoslav}, title = {Optimal Designs for Steady-state Kalman filters}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52808}, abstract = {We consider a stationary discrete-time linear process that can be observed by a finite number of sensors. The experimental design for the observations consists of an allocation of available resources to these sensors. We formalize the problem of selecting a design that maximizes the information matrix of the steady-state of the Kalman filter, with respect to a standard optimality criterion, such as \$D-\$ or \$A-\$optimality. This problem generalizes the optimal experimental design problem for a linear regression model with a finite design space and uncorrelated errors. Finally, we show that under natural assumptions, a steady-state optimal design can be computed by semidefinite programming.}, language = {en} } @misc{HarmanSagnol, author = {Harman, Radoslav and Sagnol, Guillaume}, title = {Computing D-optimal experimental designs for estimating treatment contrasts under the presence of a nuisance time trend}, issn = {1438-0064}, doi = {10.1007/978-3-319-13881-7_10}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-53640}, abstract = {We prove a mathematical programming characterisation of approximate partial D-optimality under general linear constraints. We use this characterisation with a branch-and-bound method to compute a list of all exact D-optimal designs for estimating a pair of treatment contrasts in the presence of a nuisance time trend up to the size of 24 consecutive trials.}, language = {en} } @inproceedings{HarmanSagnol, author = {Harman, Radoslav and Sagnol, Guillaume}, title = {Computing D-optimal experimental designs for estimating treatment contrasts under the presence of a nuisance time trend}, series = {Stochastic Models, Statistics and Their Applications}, volume = {122}, booktitle = {Stochastic Models, Statistics and Their Applications}, editor = {Steland, Ansgar and Rafajłowicz, Ewaryst and Szajowski, Krzysztof}, publisher = {Springer}, doi = {10.1007/978-3-319-13881-7_10}, pages = {83 -- 91}, abstract = {We prove a mathematical programming characterisation of approximate partial D-optimality under general linear constraints. We use this characterisation with a branch-and-bound method to compute a list of all exact D-optimal designs for estimating a pair of treatment contrasts in the presence of a nuisance time trend up to the size of 24 consecutive trials.}, language = {en} } @misc{DuarteSagnolOliveira, author = {Duarte, Belmiro P.M. and Sagnol, Guillaume and Oliveira, Nuno M.C.}, title = {A robust minimax Semidefinite Programming formulation for optimal design of experiments for model parametrization}, issn = {1438-0064}, doi = {10.1016/B978-0-444-63578-5.50146-8}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-54626}, abstract = {Model-based optimal design of experiments (M-bODE) is a crucial step in model parametrization since it encloses a framework that maximizes the amount of information extracted from a battery of lab experiments. We address the design of M-bODE for dynamic models considering a continuous representation of the design. We use Semidefinite Programming (SDP) to derive robust minmax formulations for nonlinear models, and extend the formulations to other criteria. The approaches are demonstrated for a CSTR where a two-step reaction occurs.}, language = {en} } @misc{BorndoerferSagnolSchwartz, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Schwartz, Stephan}, title = {An Extended Network Interdiction Problem for Optimal Toll Control}, issn = {1438-0064}, doi = {10.1016/j.endm.2016.03.040}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-55405}, abstract = {We study an extension of the shortest path network interdiction problem and present a novel real-world application in this area. We consider the problem of determining optimal locations for toll control stations on the arcs of a transportation network. We handle the fact that drivers can avoid control stations on parallel secondary roads. The problem is formulated as a mixed integer program and solved using Benders decomposition. We present experimental results for the application of our models to German motorways.}, language = {en} } @inproceedings{SagnolHarman, author = {Sagnol, Guillaume and Harman, Radoslav}, title = {Optimal Designs for Steady-state Kalman filters}, series = {Stochastic Models, Statistics and Their Applications}, volume = {122}, booktitle = {Stochastic Models, Statistics and Their Applications}, editor = {Steland, Ansgar and Rafajłowicz, Ewaryst and Szajowski, Krzysztof}, publisher = {Springer}, doi = {10.1007/978-3-319-13881-7_17}, pages = {149 -- 157}, abstract = {We consider a stationary discrete-time linear process that can be observed by a finite number of sensors. The experimental design for the observations consists of an allocation of available resources to these sensors. We formalize the problem of selecting a design that maximizes the information matrix of the steady-state of the Kalman filter, with respect to a standard optimality criterion, such as \$D-\$ or \$A-\$optimality. This problem generalizes the optimal experimental design problem for a linear regression model with a finite design space and uncorrelated errors. Finally, we show that under natural assumptions, a steady-state optimal design can be computed by semidefinite programming.}, language = {en} } @article{BorndoerferBuwayaSagnoletal., author = {Bornd{\"o}rfer, Ralf and Buwaya, Julia and Sagnol, Guillaume and Swarat, Elmar}, title = {Network spot-checking games: Theory and application to toll enforcing in transportation networks}, series = {Networks}, volume = {65}, journal = {Networks}, publisher = {Wiley Periodicals, Inc.}, doi = {10.1002/net.21596}, pages = {312 -- 328}, abstract = {We introduce the class of spot-checking games (SC games). These games model problems where the goal is to distribute fare inspectors over a toll network. In an SC game, the pure strategies of network users correspond to paths in a graph, and the pure strategies of the inspectors are subset of arcs to be controlled. Although SC games are not zero-sum, we show that a Nash equilibrium can be computed by linear programming. The computation of a strong Stackelberg equilibrium (SSE) is more relevant for this problem and we give a mixed integer programming (MIP) formulation for this problem. We show that the computation of such an equilibrium is NP-hard. More generally, we prove that it is NP-hard to compute a SSE in a polymatrix game, even if the game is pairwise zero-sum. Then, we give some bounds on the price of spite, which measures how the payoff of the inspector degrades when committing to a Nash equilibrium. Finally, we report computational experiments on instances constructed from real data, for an application to the enforcement of a truck toll in Germany. These numerical results show the efficiency of the proposed methods, as well as the quality of the bounds derived in this article.}, language = {en} } @misc{SagnolSchmidtgenanntWaldschmidtTesch, author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel and Tesch, Alexander}, title = {The Price of Fixed Assignments in Stochastic Extensible Bin Packing}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-68415}, abstract = {We consider the stochastic extensible bin packing problem (SEBP) in which \$n\$ items of stochastic size are packed into \$m\$ bins of unit capacity. In contrast to the classical bin packing problem, bins can be extended at extra cost. This problem plays an important role in stochastic environments such as in surgery scheduling: Patients must be assigned to operating rooms beforehand, such that the regular capacity is fully utilized while the amount of overtime is as small as possible. This paper focuses on essential ratios between different classes of policies: First, we consider the price of non-splittability, in which we compare the optimal non-anticipatory policy against the optimal fractional assignment policy. We show that this ratio has a tight upper bound of \$2\$. Moreover, we develop an analysis of a fixed assignment variant of the LEPT rule yielding a tight approximation ratio of \$1+1/e \approx 1.368\$ under a reasonable assumption on the distributions of job durations. Furthermore, we prove that the price of fixed assignments, which describes the loss when restricting to fixed assignment policies, is within the same factor. This shows that in some sense, LEPT is the best fixed assignment policy we can hope for.}, language = {en} } @misc{SagnolBlancoSauvage, author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibaut}, title = {Approximation Hierarchies for the cone of flow matrices}, issn = {1438-0064}, doi = {10.1016/j.endm.2018.02.002}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-68424}, abstract = {Let \$G\$ be a directed acyclic graph with \$n\$ arcs, a source \$s\$ and a sink \$t\$. We introduce the cone \$K\$ of flow matrices, which is a polyhedral cone generated by the matrices \$1_P 1_P^T \in R^{n\times n}\$, where \$1_P\in R^n\$ is the incidence vector of the \$(s,t)\$-path \$P\$. Several combinatorial problems reduce to a linear optimization problem over \$K\$. This cone is intractable, but we provide two convergent approximation hierarchies, one of them based on a completely positive representation of \$K\$. We illustrate this approach by computing bounds for a maximum flow problem with pairwise arc-capacities.}, language = {en} } @article{PronzatoSagnol, author = {Pronzato, Luc and Sagnol, Guillaume}, title = {Removing inessential points in c- and A-optimal design}, series = {Journal of Statistical Planning and Inference}, volume = {213}, journal = {Journal of Statistical Planning and Inference}, doi = {10.1016/j.jspi.2020.11.011}, pages = {233 -- 252}, abstract = {A design point is inessential when it does not contribute to an optimal design, and can therefore be safely discarded from the design space. We derive three inequalities for the detection of such inessential points in c-optimal design: the first two are direct consequences of the equivalence theorem for c-optimality; the third one is derived from a second-order cone programming formulation of c-optimal design. Elimination rules for A-optimal design are obtained as a byproduct. When implemented within an optimization algorithm, each inequality gives a screening test that may provide a substantial acceleration by reducing the size of the problem online. Several examples are presented with a multiplicative algorithm to illustrate the effectiveness of the approach.}, language = {en} } @misc{BorndoerferTeschSagnol, author = {Bornd{\"o}rfer, Ralf and Tesch, Alexander and Sagnol, Guillaume}, title = {Algorithmen unterst{\"u}tzen OP-Planung}, series = {Management \& Krankenhaus}, journal = {Management \& Krankenhaus}, number = {12}, publisher = {Wiley}, pages = {20}, abstract = {Mathematische Algorithmen k{\"o}nnen durch Vorhersage von Unsicherheiten optimierte OP-Pl{\"a}ne berechnen, sodass mehrere Zielkriterien wie {\"U}berstunden, Wartezeit und Ausf{\"a}lle im OP minimiert werden.}, language = {de} } @article{SagnolBarnerBorndoerferetal., author = {Sagnol, Guillaume and Barner, Christoph and Bornd{\"o}rfer, Ralf and Grima, Micka{\"e}l and Seeling, Mathes and Spies, Claudia and Wernecke, Klaus}, title = {Robust Allocation of Operating Rooms: a Cutting Plane Approach to handle Lognormal Case Durations}, series = {European Journal of Operational Research}, volume = {271}, journal = {European Journal of Operational Research}, number = {2}, doi = {10.1016/j.ejor.2018.05.022}, pages = {420 -- 435}, abstract = {The problem of allocating operating rooms (OR) to surgical cases is a challenging task, involving both combinatorial aspects and uncertainty handling. We formulate this problem as a parallel machines scheduling problem, in which job durations follow a lognormal distribution, and a fixed assignment of jobs to machines must be computed. We propose a cutting-plane approach to solve the robust counterpart of this optimization problem. To this end, we develop an algorithm based on fixed-point iterations that identifies worst-case scenarios and generates cut inequalities. The main result of this article uses Hilbert's projective geometry to prove the convergence of this procedure under mild conditions. We also propose two exact solution methods for a similar problem, but with a polyhedral uncertainty set, for which only approximation approaches were known. Our model can be extended to balance the load over several planning periods in a rolling horizon. We present extensive numerical experiments for instances based on real data from a major hospital in Berlin. In particular, we find that: (i) our approach performs well compared to a previous model that ignored the distribution of case durations; (ii) compared to an alternative stochastic programming approach, robust optimization yields solutions that are more robust against uncertainty, at a small price in terms of average cost; (iii) the \emph{longest expected processing time first} (LEPT) heuristic performs well and efficiently protects against extreme scenarios, but only if a good prediction model for the durations is available. Finally, we draw a number of managerial implications from these observations.}, language = {en} } @article{SagnolPauwels, author = {Sagnol, Guillaume and Pauwels, Edouard}, title = {An unexpected connection between Bayes A-optimal designs and the group lasso}, series = {Statistical Papers}, volume = {60}, journal = {Statistical Papers}, number = {2}, doi = {10.1007/s00362-018-01062-y}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-73059}, pages = {215 -- 234}, abstract = {We show that the A-optimal design optimization problem over m design points in R^n is equivalent to minimizing a quadratic function plus a group lasso sparsity inducing term over n x m real matrices. This observation allows to describe several new algorithms for A-optimal design based on splitting and block coordinate decomposition. These techniques are well known and proved powerful to treat large scale problems in machine learning and signal processing communities. The proposed algorithms come with rigorous convergence guarantees and convergence rate estimate stemming from the optimization literature. Performances are illustrated on synthetic benchmarks and compared to existing methods for solving the optimal design problem.}, language = {en} } @inproceedings{SagnolBlancoSauvage, author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibaut}, title = {Approximation Hierarchies for the cone of flow matrices}, series = {INOC 2017 - 8th International Network Optimization Conference}, volume = {64}, booktitle = {INOC 2017 - 8th International Network Optimization Conference}, doi = {10.1016/j.endm.2018.02.002}, pages = {275 -- 284}, abstract = {Let \$G\$ be a directed acyclic graph with \$n\$ arcs, a source \$s\$ and a sink \$t\$. We introduce the cone \$K\$ of flow matrices, which is a polyhedral cone generated by the matrices \$1_P 1_P^T \in R^{n\times n}\$, where \$1_P\in R^n\$ is the incidence vector of the \$(s,t)\$-path \$P\$. Several combinatorial problems reduce to a linear optimization problem over \$K\$. This cone is intractable, but we provide two convergent approximation hierarchies, one of them based on a completely positive representation of \$K\$. We illustrate this approach by computing bounds for a maximum flow problem with pairwise arc-capacities.}, language = {en} } @article{SagnolBlancoSauvage, author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibaut}, title = {The Cone of Flow Matrices: Approximation Hierarchies and Applications}, series = {Networks}, volume = {72}, journal = {Networks}, number = {1}, doi = {10.1002/net.21820}, pages = {128 -- 150}, abstract = {Let G be a directed acyclic graph with n arcs, a source s and a sink t. We introduce the cone K of flow matrices, which is a polyhedral cone generated by the matrices \$\vec{1}_P\vec{1}_P^T\in\RR^{n\times n}\$, where \$\vec{1}_P\in\RR^n\$ is the incidence vector of the (s,t)-path P. We show that several hard flow (or path) optimization problems, that cannot be solved by using the standard arc-representation of a flow, reduce to a linear optimization problem over \$\mathcal{K}\$. This cone is intractable: we prove that the membership problem associated to \$\mathcal{K}\$ is NP-complete. However, the affine hull of this cone admits a nice description, and we give an algorithm which computes in polynomial-time the decomposition of a matrix \$X\in \operatorname{span} \mathcal{K}\$ as a linear combination of some \$\vec{1}_P\vec{1}_P^T\$'s. Then, we provide two convergent approximation hierarchies, one of them based on a completely positive representation of~K. We illustrate this approach by computing bounds for the quadratic shortest path problem, as well as a maximum flow problem with pairwise arc-capacities.}, language = {en} } @article{SagnolSchmidtgenanntWaldschmidt, author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel}, title = {Restricted Adaptivity in Stochastic Scheduling}, series = {29th Annual European Symposium on Algorithms (ESA 2021)}, volume = {204}, journal = {29th Annual European Symposium on Algorithms (ESA 2021)}, doi = {10.4230/LIPIcs.ESA.2021.79}, pages = {79:1 -- 79:14}, abstract = {We consider the stochastic scheduling problem of minimizing the expected makespan on m parallel identical machines. While the (adaptive) list scheduling policy achieves an approximation ratio of 2, any (non-adaptive) fixed assignment policy has performance guarantee Ω(logm/loglogm). Although the performance of the latter class of policies are worse, there are applications in which non-adaptive policies are desired. In this work, we introduce the two classes of δ-delay and τ-shift policies whose degree of adaptivity can be controlled by a parameter. We present a policy - belonging to both classes - which is an O(loglogm)-approximation for reasonably bounded parameters. In other words, an exponential improvement on the performance of any fixed assignment policy can be achieved when allowing a small degree of adaptivity. Moreover, we provide a matching lower bound for any δ-delay and τ-shift policy when both parameters, respectively, are in the order of the expected makespan of an optimal non-anticipatory policy.}, language = {en} } @misc{Sagnol, author = {Sagnol, Guillaume}, title = {On the semidefinite representations of real functions applied to symmetric matrices}, volume = {439}, issn = {1438-0064}, doi = {10.1016/j.laa.2013.08.021}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-17511}, pages = {2829 -- 2843}, abstract = {We present a new semidefinite representation for the trace of a real function f applied to symmetric matrices, when a semidefinite representation of the convex function f is known. Our construction is intuitive, and yields a representation that is more compact than the previously known one. We also show with the help of matrix geometric means and the Riemannian metric of the set of positive definite matrices that for a rational number p in the interval (0,1], the matrix X raised to the exponent p is the largest element of a set represented by linear matrix inequalities. We give numerical results for a problem inspired from the theory of experimental designs, which show that the new semidefinite programming formulation yields a speed-up factor in the order of 10.}, language = {en} } @misc{Sagnol, author = {Sagnol, Guillaume}, title = {A Class of Semidefinite Programs with rank-one solutions}, issn = {1438-0064}, doi = {10.1016/j.laa.2011.03.027}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14933}, abstract = {We show that a class of semidefinite programs (SDP) admits a solution that is a positive semidefinite matrix of rank at most \$r\$, where \$r\$ is the rank of the matrix involved in the objective function of the SDP. The optimization problems of this class are semidefinite packing problems, which are the SDP analogs to vector packing problems. Of particular interest is the case in which our result guarantees the existence of a solution of rank one: we show that the computation of this solution actually reduces to a Second Order Cone Program (SOCP). We point out an application in statistics, in the optimal design of experiments.}, language = {en} } @misc{BorndoerferSagnolSwarat, author = {Bornd{\"o}rfer, Ralf and Sagnol, Guillaume and Swarat, Elmar}, title = {A Case Study on Optimizing Toll Enforcements on Motorways}, issn = {1438-0064}, doi = {10.4230/OASIcs.SCOR.2012.1}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-15498}, abstract = {In this paper we present the problem of computing optimal tours of toll inspectors on German motorways. This problem is a special type of vehicle routing problem and builds up an integrated model, consisting of a tour planning and a duty rostering part. The tours should guarantee a network-wide control whose intensity is proportional to given spatial and time dependent traffic distributions. We model this using a space-time network and formulate the associated optimization problem by an integer program (IP). Since sequential approaches fail, we integrated the assignment of crews to the tours in our model. In this process all duties of a crew member must fit in a feasible roster. It is modeled as a Multi-Commodity Flow Problem in a directed acyclic graph, where specific paths correspond to feasible rosters for one month. We present computational results in a case-study on a German subnetwork which documents the practicability of our approach.}, language = {en} } @misc{BorndoerferBuwayaSagnoletal., author = {Bornd{\"o}rfer, Ralf and Buwaya, Julia and Sagnol, Guillaume and Swarat, Elmar}, title = {Optimizing Toll Enforcement in Transportation Networks: a Game-Theoretic Approach}, issn = {1438-0064}, doi = {/10.1016/j.endm.2013.05.100}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-17401}, abstract = {We present a game-theoretic approach to optimize the strategies of toll enforcement on a motorway network. In contrast to previous approaches, we consider a network with an arbitrary topology, and we handle the fact that users may choose their Origin-Destination path; in particular they may take a detour to avoid sections with a high control rate. We show that a Nash equilibrium can be computed with an LP (although the game is not zero-sum), and we give a MIP for the computation of a Stackelberg equilibrium. Experimental results based on an application to the enforcement of a truck toll on German motorways are presented.}, language = {en} } @misc{Sagnol, author = {Sagnol, Guillaume}, title = {Picos Documentation. Release 0.1.1.}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-17396}, abstract = {PICOS is a user friendly interface to several conic and integer programming solvers, very much like YALMIP under MATLAB. The main motivation for PICOS is to have the possibility to enter an optimization problem as a high level model, and to be able to solve it with several different solvers. Multidimensional and matrix variables are handled in a natural fashion, which makes it painless to formulate a SDP or a SOCP. This is very useful for educational purposes, and to quickly implement some models and test their validity on simple examples. Furthermore, with PICOS you can take advantage of the python programming language to read and write data, construct a list of constraints by using python list comprehensions, take slices of multidimensional variables, etc.}, language = {en} } @article{DuarteSagnol, author = {Duarte, Belmiro and Sagnol, Guillaume}, title = {Approximate and exact optimal designs for 2^k factorial experiments for generalized linear models via second order cone programming}, series = {Statistical Papers}, volume = {61}, journal = {Statistical Papers}, doi = {10.1007/s00362-018-01075-7}, pages = {2737 -- 2767}, abstract = {Model-based optimal designs of experiments (M-bODE) for nonlinear models are typically hard to compute. The literature on the computation of M-bODE for nonlinear models when the covariates are categorical variables, i.e. factorial experiments, is scarce. We propose second order cone programming (SOCP) and Mixed Integer Second Order Programming (MISOCP) formulations to find, respectively, approximate and exact A- and D-optimal designs for 2𝑘 factorial experiments for Generalized Linear Models (GLMs). First, locally optimal (approximate and exact) designs for GLMs are addressed using the formulation of Sagnol (J Stat Plan Inference 141(5):1684-1708, 2011). Next, we consider the scenario where the parameters are uncertain, and new formulations are proposed to find Bayesian optimal designs using the A- and log det D-optimality criteria. A quasi Monte-Carlo sampling procedure based on the Hammersley sequence is used for computing the expectation in the parametric region of interest. We demonstrate the application of the algorithm with the logistic, probit and complementary log-log models and consider full and fractional factorial designs.}, language = {en} } @inproceedings{SagnolSchmidtgenanntWaldschmidtTesch, author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel and Tesch, Alexander}, title = {The Price of Fixed Assignments in Stochastic Extensible Bin Packing}, series = {WAOA 2018: Approximation and Online Algorithms}, volume = {11312}, booktitle = {WAOA 2018: Approximation and Online Algorithms}, doi = {10.1007/978-3-030-04693-4_20}, pages = {327 -- 347}, abstract = {We consider the stochastic extensible bin packing problem (SEBP) in which n items of stochastic size are packed into m bins of unit capacity. In contrast to the classical bin packing problem, the number of bins is fixed and they can be extended at extra cost. This problem plays an important role in stochastic environments such as in surgery scheduling: Patients must be assigned to operating rooms beforehand, such that the regular capacity is fully utilized while the amount of overtime is as small as possible. This paper focuses on essential ratios between different classes of policies: First, we consider the price of non-splittability, in which we compare the optimal non-anticipatory policy against the optimal fractional assignment policy. We show that this ratio has a tight upper bound of 2. Moreover, we develop an analysis of a fixed assignment variant of the LEPT rule yielding a tight approximation ratio of (1+e-1)≈1.368 under a reasonable assumption on the distributions of job durations. Furthermore, we prove that the price of fixed assignments, related to the benefit of adaptivity, which describes the loss when restricting to fixed assignment policies, is within the same factor. This shows that in some sense, LEPT is the best fixed assignment policy we can hope for.}, language = {en} }