Send-and-split method for minimum-concave-cost network flows
Mathematics of Operations Research
Integer and combinatorial optimization
Integer and combinatorial optimization
Solving multi-item capacitated lot-sizing problems using variable redefinition
Operations Research
Capacitated lot sizing with setup times
Management Science
Polyhedra for lot-sizing with Wagner-Whitin costs
Mathematical Programming: Series A and B
A cutting plane approach to capacitated lot-sizing with start-up costs
Mathematical Programming: Series A and B
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
bc -- prod: A Specialized Branch-and-Cut System for Lot-Sizing Problems
Management Science
Introduction to Computational Optimization Models for Production Planning in a Supply Chain
Introduction to Computational Optimization Models for Production Planning in a Supply Chain
Computers and Operations Research
Matheuristics: Hybridizing Metaheuristics and Mathematical Programming
Matheuristics: Hybridizing Metaheuristics and Mathematical Programming
A generic view of Dantzig-Wolfe decomposition in mixed integer programming
Operations Research Letters
A math-heuristic dantzig-wolfe algorithm for the capacitated lot sizing problem
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
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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.