TY - GEN A1 - Büsing, Christina A1 - D'Andreagiovanni, Fabio A1 - Raymond, Annie T1 - 0-1 Multiband Robust Optimization N2 - We provide an overview of new theoretical results that we obtained while further investigating multiband robust optimization, a new model for robust optimization that we recently proposed to tackle uncertainty in mixed-integer linear programming. This new model extends and refines the classical Gamma-robustness model of Bertsimas and Sim and is particularly useful in the common case of arbitrary asymmetric distributions of the uncertainty. Here, we focus on uncertain 0-1 programs and we analyze their robust counterparts when the uncertainty is represented through a multiband set. Our investigations were inspired by the needs of our industrial partners in the research project ROBUKOM. T3 - ZIB-Report - 13-77 KW - Combinatorial Optimization, Robust Optimization, Multiband Robustness, Network Design Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-44093 SN - 1438-0064 ER - TY - THES A1 - Shestakov, Alexey T1 - A Deep Learning Method for Automated Detection of Meniscal Tears in Meniscal Sub-Regions in 3D MRI Data N2 - This work presents a fully automated pipeline, centered around a deep neural network, as well as a method to train that network in an efficient manner, that enables accurate detection of lesions in meniscal anatomical subregions. The network architecture is based on a transformer encoder/decoder. It is trained on DESS and tuned on IW TSE 3D MRI scans sourced from the Osteoarthritis Initiative. Furthermore, it is trained in a multilabel, and multitask fashion, using an auxiliary detection head. The former enables implicit localisation of meniscal defects, that to the best of my knowledge, has not yet been reported elsewhere. The latter enables efficient learning on the entire 3D MRI volume. Thus, the proposed method does not require any expert knowledge at inference. Aggregated inference results from two datasets resulted in an overall AUCROC result of 0.90, 0.91 and 0.93 for meniscal lesion detection anywhere in the knee, in medial and in lateral menisci respectively. These results compare very well to the related work, even though only a fraction of the data has been utilized. Clinical applicability and benefit is yet to be determined. KW - Machine Learning KW - Computational Diagnosis KW - Knee Osteoarthritis Y1 - 2021 ER - TY - GEN A1 - D'Andreagiovanni, Fabio A1 - Krolikowski, Jonatan A1 - Pulaj, Jonad T1 - A hybrid primal heuristic for Robust Multiperiod Network Design N2 - We investigate the Robust Multiperiod Network Design Problem, a generalization of the classical Capacitated Network Design Problem that additionally considers multiple design periods and provides solutions protected against traffic uncertainty. Given the intrinsic difficulty of the problem, which proves challenging even for state-of-the art commercial solvers, we propose a hybrid primal heuristic based on the combination of ant colony optimization and an exact large neighborhood search. Computational experiments on a set of realistic instances from the SNDlib show that our heuristic can find solutions of extremely good quality with low optimality gap. T3 - ZIB-Report - 13-78 KW - Multiperiod Network Design, Traffic Uncertainty, Robust Optimization, Multiband Robustness, Hybrid Heuristics Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-44081 SN - 1438-0064 ER - TY - GEN A1 - Paskin, Martha A1 - Baum, Daniel A1 - Dean, Mason N. A1 - von Tycowicz, Christoph T1 - A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks -- Source Code and Data N2 - Source code and novel dataset of basking shark head skeletons facilitating the reproduction of the results presented in 'A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks' - ECCV 2022. Y1 - 2022 U6 - https://doi.org/10.12752/8730 ER - TY - GEN A1 - Büsing, Christina A1 - D'Andreagiovanni, Fabio T1 - A new theoretical framework for Robust Optimization under multi-band uncertainty N2 - We provide an overview of our main results about studying Linear Programming Problems whose coefficient matrix is subject to uncertainty and the uncertainty is modeled through a multi-band set. Such an uncertainty set generalizes the classical one proposed by Bertsimas and Sim and is particularly suitable in the common case of arbitrary non-symmetric distributions of the parameters. Our investigations were inspired by practical needs of our industrial partner in ongoing projects with focus on the design of robust telecommunications networks. T3 - ZIB-Report - 13-61 KW - Robust Optimization, Uncertainty Set, Multiband Robustness, Network Design Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-42644 UR - http://www.springer.com/business+%26+management/operations+research/book/978-3-319-00794-6 SN - 1438-0064 ER - TY - GEN A1 - Hosoda, Junko A1 - Maher, Stephen J. A1 - Shinano, Yuji A1 - Villumsen, Jonas Christoffer T1 - A parallel branch-and-bound heuristic for the integrated long-haul and local vehicle routing problem on an adaptive transportation network N2 - Consolidation of commodities and coordination of vehicle routes are fundamental features of supply chain management problems. While locations for consolidation and coordination are typically known a priori, in adaptive transportation networks this is not the case. The identification of such consolidation locations forms part of the decision making process. Supply chain management problems integrating the designation of consolidation locations with the coordination of long haul and local vehicle routing is not only challenging to solve, but also very difficult to formulate mathematically. In this paper, the first mathematical model integrating location clustering with long haul and local vehicle routing is proposed. This mathematical formulation is used to develop algorithms to find high quality solutions. A novel parallel framework is developed that combines exact and heuristic methods to improve the search for high quality solutions and provide valid bounds. The results demonstrate that using exact methods to guide heuristic search is an effective approach to find high quality solutions for difficult supply chain management problems. T3 - ZIB-Report - 23-02 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-89700 SN - 1438-0064 ER - TY - GEN A1 - Wolf, Thomas T1 - A Study of Genetic Algorithms solving a combinatorial Puzzle N2 - The suitability of Genetic Algorithms (GAs) to solve a combinatorial problem with only one solution is investigated. The dependence of the performance is studied for GA-hard and GA-soft fitness functions, both with a range of different parameter values and different encodings. T3 - ZIB-Report - SC-98-01 Y1 - 1998 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-3445 ER - TY - GEN A1 - Pfeuffer, Frank A1 - Werner, Axel T1 - Adaptive telecommunication network operation with a limited number of reconfigurations N2 - Rising traffic in telecommunication networks lead to rising energy costs for the network operators. Meanwhile, increased flexibility of the networking hardware may help to realize load-adaptive operation of the networks to cut operation costs. To meet network operators’ concerns over stability, we propose to switch network configurations only a limited number of times per day. We present a method for the integrated computation of optimal switching times and network configurations that alternatingly solves mixed-integer programs and constrained shortest cycle problems in a certain graph. Similarly to the Branch & Bound Algorithm, it uses lower and upper bounds on the optimum value and allows for pivoting strategies to guide the computation and avoid the solution of irrelevant subproblems. The algorithm can act as a framework to be adapted and applied to suitable problems of different origin. T3 - ZIB-Report - 15-36 KW - Telecommunication KW - Network Design KW - Dynamic Traffic KW - Branch and Bound Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-55547 SN - 1438-0064 ER - TY - GEN A1 - Quer, Jannes A1 - Donati, Luca A1 - Keller, Bettina A1 - Weber, Marcus T1 - An automatic adaptive importance sampling algorithm for molecular dynamics in reaction coordinates N2 - In this article we propose an adaptive importance sampling scheme for dynamical quantities of high dimensional complex systems which are metastable. The main idea of this article is to combine a method coming from Molecular Dynamics Simulation, Metadynamics, with a theorem from stochastic analysis, Girsanov's theorem. The proposed algorithm has two advantages compared to a standard estimator of dynamic quantities: firstly, it is possible to produce estimators with a lower variance and, secondly, we can speed up the sampling. One of the main problems for building importance sampling schemes for metastable systems is to find the metastable region in order to manipulate the potential accordingly. Our method circumvents this problem by using an assimilated version of the Metadynamics algorithm and thus creates a non-equilibrium dynamics which is used to sample the equilibrium quantities. T3 - ZIB-Report - 17-09 KW - Adaptive Importance Sampling KW - Molecular Dynamics KW - Metastability KW - Variance Reduction KW - Non Equilibrium Sampling KW - Metadynamics KW - Girsanov Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62075 SN - 1438-0064 ER - TY - GEN A1 - Fujii, Koichi A1 - Kim, Sunyoung A1 - Kojima, Masakazu A1 - Mittelmann, Hans D. A1 - Shinano, Yuji T1 - An Exceptionally Difficult Binary Quadratic Optimization Problem with Symmetry: a Challenge for The Largest Unsolved QAP Instance Tai256c N2 - Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original QAP, the conversion increases the possibility to solve the QAP. Solving exactly the BQOP, however, is still very difficult. Indeed, a 1.48% gap remains between the best known upper bound (UB) and lower bound (LB) of the unknown optimal value. This paper shows that the BQOP admits a nontrivial symmetry, a property that makes the BQOP very hard to solve. The symmetry induces equivalent subproblems in branch and bound (BB) methods. To effectively improve the LB, we propose an efficient BB method that incorporates a doubly nonnegative relaxation, the standard orbit branching and a technique to prune equivalent subproblems. With this BB method, a new LB with 1.25% gap is successfully obtained, and computing an LB with 1.0% gap is shown to be still quite difficult. T3 - ZIB-Report - 23-27 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-93072 SN - 1438-0064 ER -