@unpublished{BeckSchmidtThueraufetal.2022, author = {Beck, Yasmine and Schmidt, Martin and Th{\"u}rauf, Johannes and Bienstock, Daniel}, title = {On a Computationally Ill-Behaved Bilevel Problem with a Continuous and Nonconvex Lower Level}, pages = {16}, year = {2022}, abstract = {It is well known that bilevel optimization problems are hard to solve both in theory and practice. In this paper, we highlight a further computational difficulty when it comes to solving bilevel problems with continuous but nonconvex lower levels. Even if the lower-level problem is solved to ɛ-feasibility regarding its nonlinear constraints for an arbitrarily small but positive ɛ, the obtained bilevel solution as well as its objective value may be arbitrarily far away from the actual bilevel solution and its actual objective value. This result even holds for bilevel problems for which the nonconvex lower level is uniquely solvable, for which the strict complementarity condition holds, for which the feasible set is convex, and for which Slater's constraint qualification is satisfied for all feasible upper-level decisions. Since the consideration of ɛ-feasibility cannot be avoided when solving nonconvex problems to global optimality, our result shows that computational bilevel optimization with continuous and nonconvex lower levels needs to be done with great care. Finally, we illustrate that the nonlinearities in the lower level are the key reason for the observed bad behavior by showing that linear bilevel problems behave much better at least on the level of feasible solutions.}, language = {en} } @unpublished{GoerigkKurtzSchmidtetal.2023, author = {Goerigk, Marc and Kurtz, Jannis and Schmidt, Martin and Th{\"u}rauf, Johannes}, title = {Connections between Robust and Bilevel Optimization}, pages = {22}, year = {2023}, abstract = {Robust and bilevel optimization share the common feature that they involve a certain multilevel structure. Hence, although they model something rather different when used in practice, they seem to have a similar mathematical structure. In this paper, we analyze the connections between different types of robust problems (static robust problems with and without decision-dependence of their uncertainty sets, worst-case regret problems, and two-stage robust problems) as well as of bilevel problems (optimistic problems, pessimistic problems, and robust bilevel problems). It turns out that bilevel optimization seems to be more general in the sense that for most types of robust problems, one can find proper reformulations as bilevel problems but not necessarily the other way around. We hope that these results pave the way for a stronger connection between the two fields - in particular to use both theory and algorithms from one field in the other and vice versa.}, language = {en} } @article{GruebelKleinertKrebsetal.2019, author = {Gr{\"u}bel, Julia and Kleinert, Thomas and Krebs, Vanessa and Orlinskaya, Galina and Schewe, Lars and Schmidt, Martin and Th{\"u}rauf, Johannes}, title = {On Electricity Market Equilibria with Storage: Modeling, Uniqueness, and a Distributed ADMM}, series = {Computers \& Operations Research}, journal = {Computers \& Operations Research}, number = {114}, doi = {10.1016/j.cor.2019.104783}, year = {2019}, abstract = {We consider spot-market trading of electricity including storage operators as additional agents besides producers and consumers. Storages allow for shifting produced electricity from one time period to a later one. Due to this, multiple market equilibria may occur even if classical uniqueness assumptions for the case without storages are satisfied. For models containing storage operators, we derive sufficient conditions that ensure uniqueness of generation and demand. We also prove uniqueness of the market equilibrium for the special case of a single storage operator. Nevertheless, in case of multiple storage operators, uniqueness fails to hold in general, which we show by illustrative examples. We conclude the theoretical discussion with a general ex-post condition for proving the uniqueness of a given solution. In contrast to classical settings without storages, the computation of market equilibria is much more challenging since storage operations couple all trading events over time. For this reason, we propose a tailored parallel and distributed alternating direction method of multipliers (ADMM) for efficiently computing spot-market equilibria over long time horizons. We first analyze the parallel performance of the method itself. Finally, we show that the parallel ADMM clearly outperforms solving the respective problems directly and that it is capable of solving instances with more than 42 million variables in less than 13 minutes.}, language = {en} } @article{LabbePleinSchmidtetal.2019, author = {Labb{\´e}, Martine and Plein, Fr{\"a}nk and Schmidt, Martin and Th{\"u}rauf, Johannes}, title = {Deciding Feasibility of a Booking in the European Gas Market on a Cycle is in P for the Case of Passive Networks}, series = {Networks}, volume = {78}, journal = {Networks}, number = {2}, doi = {10.1007/s00186-021-00752-y}, pages = {128 -- 152}, year = {2019}, abstract = {We show that the feasibility of a booking in the European entry-exit gas market can be decided in polynomial time on single-cycle networks that are passive, i.e., do not contain controllable elements. The feasibility of a booking can be characterized by solving polynomially many nonlinear potential-based flow models for computing so-called potential-difference maximizing load flow scenarios. We thus analyze the structure of these models and exploit both the cyclic graph structure as well as specific properties of potential-based flows. This enables us to solve the decision variant of the nonlinear potential-difference maximization by reducing it to a system of polynomials of constant dimension that is independent of the cycle's size. This system of fixed dimension can be handled with tools from real algebraic geometry to derive a polynomial-time algorithm. The characterization in terms of potential-difference maximizing load flow scenarios then leads to a polynomial-time algorithm for deciding the feasibility of a booking. Our theoretical results extend the existing knowledge about the complexity of deciding the feasibility of bookings from trees to single-cycle networks.}, language = {en} } @unpublished{LiersScheweThuerauf2019, author = {Liers, Frauke and Schewe, Lars and Th{\"u}rauf, Johannes}, title = {Radius of Robust Feasibility for Mixed-Integer Problems}, publisher = {Informs Journal on Computing}, doi = {10.1287/ijoc.2020.1030}, year = {2019}, abstract = {For a mixed-integer linear problem (MIP) with uncertain constraints, the radius of robust feasibility (RRF) determines a value for the maximal "size" of the uncertainty set such that robust feasibility of the MIP can be guaranteed. The approaches for the RRF in the literature are restricted to continuous optimization problems. We first analyze relations between the RRF of a MIP and its continuous linear (LP) relaxation. In particular, we derive conditions under which a MIP and its LP relaxation have the same RRF. Afterward, we extend the notion of the RRF such that it can be applied to a large variety of optimization problems and uncertainty sets. In contrast to the setting commonly used in the literature, we consider for every constraint a potentially different uncertainty set that is not necessarily full-dimensional. Thus, we generalize the RRF to MIPs as well as to include "safe" variables and constraints, i.e., where uncertainties do not affect certain variables or constraints. In the extended setting, we again analyze relations between the RRF for a MIP and its LP relaxation. Afterward, we present methods for computing the RRF of LPs as well as of MIPs with safe variables and constraints. Finally, we show that the new methodologies can be successfully applied to the instances in the MIPLIB 2017 for computing the RRF.}, language = {en} } @article{PleinThueraufLabbeetal.2021, author = {Plein, Fr{\"a}nk and Th{\"u}rauf, Johannes and Labb{\´e}, Martine and Schmidt, Martin}, title = {A Bilevel Optimization Approach to Decide the Feasibility of Bookings in the European Gas Market}, series = {Mathematical Methods of Operations Research}, journal = {Mathematical Methods of Operations Research}, doi = {10.1007/s00186-021-00752-y}, pages = {37}, year = {2021}, abstract = {The European gas market is organized as a so-called entry-exit system with the main goal to decouple transport and trading. To this end, gas traders and the transmission system operator (TSO) sign so-called booking contracts that grant capacity rights to traders to inject or withdraw gas at certain nodes up to this capacity. On a day-ahead basis, traders then nominate the actual amount of gas within the previously booked capacities. By signing a booking contract, the TSO guarantees that all nominations within the booking bounds can be transported through the network. This results in a highly challenging mathematical problem. Using potential-based flows to model stationary gas physics, feasible bookings on passive networks, i.e., networks without controllable elements, have been characterized in the recent literature. In this paper, we consider networks with linearly modeled active elements such as compressors or control valves. Since these active elements allow the TSO to control the gas flow, the single-level approaches for passive networks from the literature are no longer applicable. We thus present a bilevel model to decide the feasibility of bookings in networks with active elements. While this model is well-defined for general active networks, we focus on the class of networks for which active elements do not lie on cycles. This assumption allows us to reformulate the original bilevel model such that the lower-level problem is linear for every given upper-level decision. Consequently, we derive several single-level reformulations for this case. Besides the classic Karush-Kuhn-Tucker reformulation, we obtain three problem-specific optimal-value-function reformulations. The latter also lead to novel characterizations of feasible bookings in networks with active elements that do not lie on cycles. We compare the performance of our methods by a case study based on data from the GasLib.}, language = {en} } @article{ReussWelderThueraufetal.2019, author = {Reuß, Markus and Welder, Lara and Th{\"u}rauf, Johannes and Linßen, Jochen and Grube, Thomas and Schewe, Lars and Schmidt, Martin and Stolten, Detlef and Robinius, Martin}, title = {Modeling Hydrogen Networks for Future Energy Systems: A Comparison of Linear and Nonlinear Approaches}, series = {International Journal of Hydrogen Energy}, journal = {International Journal of Hydrogen Energy}, doi = {10.1016/j.ijhydene.2019.10.080}, year = {2019}, abstract = {Common energy system models that integrate hydrogen transport in pipelines typically simplify fluid flow models and reduce the network size in order to achieve solutions quickly. This contribution analyzes two different types of pipeline network topologies (namely, star and tree networks) and two different fluid flow models (linear and nonlinear) for a given hydrogen capacity scenario of electrical reconversion in Germany to analyze the impact of these simplifications. For each network topology, robust demand and supply scenarios are generated. The results show that a simplified topology, as well as the consideration of detailed fluid flow, could heavily influence the total pipeline investment costs. For the given capacity scenario, an overall cost reduction of the pipeline costs of 37\% is observed for the star network with linear cost compared to the tree network with nonlinear fluid flow. The impact of these improvements regarding the total electricity reconversion costs has led to a cost reduction of 1.4\%, which is fairly small. Therefore, the integration of nonlinearities into energy system optimization models is not recommended due to their high computational burden. However, the applied method for generating robust demand and supply scenarios improved the credibility and robustness of the network topology, while the simplified fluid flow consideration can lead to infeasibilities. Thus, we suggest the utilization of the nonlinear model for post- processing to prove the feasibility of the results and strengthen their credibility, while retaining the computational performance of linear modeling.}, language = {en} } @article{RobiniusScheweSchmidtetal.2018, author = {Robinius, Martin and Schewe, Lars and Schmidt, Martin and Stolten, Detlef and Th{\"u}rauf, Johannes and Welder, Lara}, title = {Robust Optimal Discrete Arc Sizing for Tree-Shaped Potential Networks}, series = {Computational Optimization and Applications}, journal = {Computational Optimization and Applications}, number = {73(3)}, doi = {10.1007/s10589-019-00085-x}, pages = {791 -- 819}, year = {2018}, abstract = {We consider the problem of discrete arc sizing for tree-shaped potential networks with respect to infinitely many demand scenarios. This means that the arc sizes need to be feasible for an infinite set of scenarios. The problem can be seen as a strictly robust counterpart of a single-scenario network design problem, which is shown to be NP-complete even on trees. In order to obtain a tractable problem, we introduce a method for generating a finite scenario set such that optimality of a sizing for this finite set implies the sizing's optimality for the originally given infinite set of scenarios. We further prove that the size of the finite scenario set is quadratically bounded above in the number of nodes of the underlying tree and that it can be computed in polynomial time. The resulting problem can then be solved as a standard mixed-integer linear optimization problem. Finally, we show the applicability of our theoretical results by computing globally optimal arc sizes for a realistic hydrogen transport network of Eastern Germany.}, language = {en} } @article{ScheweSchmidtThuerauf, author = {Schewe, Lars and Schmidt, Martin and Th{\"u}rauf, Johannes}, title = {Global Optimization for the Multilevel European Gas Market System with Nonlinear Flow Models on Trees}, series = {Journal of Global Optimization}, journal = {Journal of Global Optimization}, doi = {10.1007/s10898-021-01099-8}, abstract = {The European gas market is implemented as an entry-exit system, which aims to decouple transport and trading of gas. It has been modeled in the literature as a multilevel problem, which contains a nonlinear flow model of gas physics. Besides the multilevel structure and the nonlinear flow model, the computation of so-called technical capacities is another major challenge. These lead to nonlinear adjustable robust constraints that are computationally intractable in general. We provide techniques to equivalently reformulate these nonlinear adjustable constraints as finitely many convex constraints including integer variables in the case that the underlying network is tree-shaped. We further derive additional combinatorial constraints that significantly speed up the solution process. Using our results, we can recast the multilevel model as a single-level nonconvex mixed-integer nonlinear problem, which we then solve on a real-world network, namely the Greek gas network, to global optimality. Overall, this is the first time that the considered multilevel entry-exit system can be solved for a real-world sized network and a nonlinear flow model.}, language = {en} } @article{ScheweSchmidtThuerauf2018, author = {Schewe, Lars and Schmidt, Martin and Th{\"u}rauf, Johannes}, title = {Structural Properties of Feasible Bookings in the European Entry-Exit Gas Market System}, series = {4OR}, journal = {4OR}, number = {18}, doi = {10.1007/s10288-019-00411-3}, pages = {197 -- 218}, year = {2018}, abstract = {In this work we analyze the structural properties of the set of feasible bookings in the European entry-exit gas market system. We present formal definitions of feasible bookings and then analyze properties that are important if one wants to optimize over them. Thus, we study whether the sets of feasible nominations and bookings are bounded, convex, connected, conic, and star-shaped. The results depend on the specific model of gas flow in a network. Here, we discuss a simple linear flow model with arc capacities as well as nonlinear and mixed-integer nonlinear models of passive and active networks, respectively. It turns out that the set of feasible bookings has some unintuitive properties. For instance, we show that the set is nonconvex even though only a simple linear flow model is used.}, language = {en} }