Solving a dynamic facility location problem with partial closing and reopening

Motivated by an industrial application, we consider a recently introduced multi-period facility location problem with multiple commodities and multiple capacity levels. The problem allows for the relocation of facilities, as well as for the temporary closing of parts of the facilities, while other p...

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Bibliographic Details
Published in:Computers & operations research Vol. 67; pp. 143 - 154
Main Authors: Jena, Sanjay Dominik, Cordeau, Jean-François, Gendron, Bernard
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.03.2016
Pergamon Press Inc
Subjects:
Commodities
Computing time
Demand
Dynamic capacity adjustment
Facility location
Heuristic
Industrial application
Integer programming
Lagrange multiplier
Lagrangian relaxation
Mathematical models
Mixed-integer programming
Operations research
Programming
Relocation of industry
Site selection
Studies
Facility location
Dynamic capacity adjustment
Lagrangian relaxation
Mixed-integer programming
Industrial application
ISSN:0305-0548, 1873-765X, 0305-0548
Online Access:Get full text
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Summary:Motivated by an industrial application, we consider a recently introduced multi-period facility location problem with multiple commodities and multiple capacity levels. The problem allows for the relocation of facilities, as well as for the temporary closing of parts of the facilities, while other parts remain open. In addition, it uses particular capacity constraints that involve integer rounding of the allocated demands. In this paper, we propose a strong formulation for the problem, as well as a hybrid heuristic that first applies Lagrangian relaxation and then constructs a restricted mixed-integer programming model based on the previously obtained Lagrangian solutions. Computational results for large-scale instances emphasize the usefulness of the heuristic in practice. While general-purpose mixed-integer programming solvers do not find feasible solutions for about half of the instances, the heuristic consistently provides high-quality solutions in short computing times, as well as tight bounds on their optimality. •We provide a new formulation for a complex multi-period facility location that allows for the partial closing and reopening of facilities.•The new formulation provides integrality gaps that are, on average, 29 times smaller than those of traditional formulations.•We develop a Lagrangian relaxation based heuristic, able to solve large-scale problem instances for which state-of-the-art mixed integer programming solvers do not find feasible solutions.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2015.10.011