Knapsack Problems with Setups
MICHEL, Sophie
Laboratoire de Mathématiques Appliquées du Havre [LMAH]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Laboratoire de Mathématiques Appliquées du Havre [LMAH]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
VANDERBECK, François
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]
MICHEL, Sophie
Laboratoire de Mathématiques Appliquées du Havre [LMAH]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Laboratoire de Mathématiques Appliquées du Havre [LMAH]
Reformulations based algorithms for Combinatorial Optimization [Realopt]
VANDERBECK, François
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]
< Réduire
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]
Langue
en
Article de revue
Ce document a été publié dans
European Journal of Operational Research. 2009, vol. 196, p. 909-918
Elsevier
Résumé en anglais
Knapsack problems with setups find their application in many concrete industrial and financial problems. Moreover, they also arise as subproblems in a Dantzig-Wolfe decomposition approach to more complex combinatorial ...Lire la suite >
Knapsack problems with setups find their application in many concrete industrial and financial problems. Moreover, they also arise as subproblems in a Dantzig-Wolfe decomposition approach to more complex combinatorial optimization problems, where they need to be solved repeatedly and therefore efficiently. Here, we consider the multiple-class integer knapsack problem with setups. Items are partitioned into classes whose use implies a setup cost and associated capacity consumption. Item weights are assumed to be a multiple of their class weight. The total weight of selected items and setups is bounded. The objective is to maximize the difference between the profits of selected items and the fixed costs incurred for setting-up classes. A special case is the bounded integer knapsack problem with setups where each class holds a single item and its continuous version where a fraction of an item can be selected while incurring a full setup. The paper shows the extent to which classical results for the knapsack problem can be generalized to these variants with setups. In particular, an extension of the branch-and-bound algorithm of Horowitz and Sahni is developed for problems with positive setup costs. Our direct approach is compared experimentally with the approach proposed in the literature consisting in converting the problem into a multiple choice knapsack with pseudo-polynomial size.< Réduire
Mots clés en anglais
Knapsack problem
fixed cost
setup
variable upper bound
branch-and-bound
Origine
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