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A math-heuristic Dantzig-Wolfe algorithm for capacitated lot sizing

A math-heuristic Dantzig-Wolfe algorithm for capacitated lot sizing The multi-item multi-period capacitated lot sizing problem with setups (CLST) is a well known optimization problem with wide applicability in real-world production planning problems. Based on a recently proposed Dantzig-Wolfe approach we present a novel math-heuristic algorithm for the CLST. The major contribution of this paper lies in the presentation of an algorithm that exploits exact techniques (Dantzig-Wolfe) in a metaheuristic fashion, in line with the novel trend of math-heuristic algorithms. To the best of the authors’ knowledge, it is the first time that such technique is employed within a metaheuristic framework, with the aim of tackling challenging instances in short computational time. Moreover, we provide reasoning that the approach may be beneficial when additional constraints like perishability constraints are added. This also constitutes an important extension when looking at it from the view of solution methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

A math-heuristic Dantzig-Wolfe algorithm for capacitated lot sizing

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References (25)

Publisher
Springer Journals
Copyright
Copyright © 2013 by Springer Science+Business Media Dordrecht
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Mathematics, general; Computer Science, general; Statistical Physics, Dynamical Systems and Complexity
ISSN
1012-2443
eISSN
1573-7470
DOI
10.1007/s10472-013-9339-9
Publisher site
See Article on Publisher Site

Abstract

The multi-item multi-period capacitated lot sizing problem with setups (CLST) is a well known optimization problem with wide applicability in real-world production planning problems. Based on a recently proposed Dantzig-Wolfe approach we present a novel math-heuristic algorithm for the CLST. The major contribution of this paper lies in the presentation of an algorithm that exploits exact techniques (Dantzig-Wolfe) in a metaheuristic fashion, in line with the novel trend of math-heuristic algorithms. To the best of the authors’ knowledge, it is the first time that such technique is employed within a metaheuristic framework, with the aim of tackling challenging instances in short computational time. Moreover, we provide reasoning that the approach may be beneficial when additional constraints like perishability constraints are added. This also constitutes an important extension when looking at it from the view of solution methods.

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Mar 28, 2013

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