Learning about Farkas' lemma and how it can inform Benders decomposition to learn from infeasibility, applied to the capacitated facility location problem. The post How Benders Decomposition Works, Part II: Feasibility Cuts appeared first on Towards Data Science .
By Luis Fernando Pérez Armas
arXiv:2606. 07403v1 Announce Type: cross Abstract: Benders decomposition is a fundamental framework for solving large-scale mixed-integer optimization problems with complicating variables that, when fixed, yield significantly easier subproblems.
By Changkun Guan, El Mehdi Er Raqabi, Mathieu Tanneau, Pascal Van Hentenryck
arXiv:2601. 06542v2 Announce Type: replace-cross Abstract: In this paper, we investigate the Resource-Constrained Project Scheduling Problem (RCPSP) with Time-of-Use (TOU) energy tariffs and machine states, a variant of RCPSP for production scheduling, where energy price is part of the criteria and one highly energy-demanding machine can be in one of the following three states: proc, idle, or off.
By Corentin Juvigny, Anton\'in Nov\'ak, Jan Mand\'ik, Zden\v{e}k Hanz\'alek
arXiv:2608. 11230v1 Announce Type: new Abstract: This paper introduces the edge-based contiguous p-median (ECpM) problem to partition the roads in a network into a given number of compact and contiguous territories.
By Zeyad Kassem, Adolfo R. Escobedo
arXiv:2607. 22550v1 Announce Type: cross Abstract: We propose a learning-augmented Benders decomposition framework to solve large-scale two-stage stochastic mixed-integer programs.
By Seung Jin Choi, Kimiya Jozani, Josh Cooper, Esra Buyuktahtakin Toy
arXiv:2607. 13218v1 Announce Type: cross Abstract: In this work, we study various graph partitioning problems under a general demand model.
By Micha{\l} Szyfelbein, Dariusz Dereniowski