Multiple objective branch and bound for mixed 0-1 linear programming: Corrections and improvements for the biobjective case

This work addresses the correction and improvement of Mavrotas and Diakoulaki's branch and bound algorithm for mixed 0-1 multiple objective linear programs. We first elaborate the issues encountered by the original algorithm and then propose a corrected version for the biobjective case using an...

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Bibliographic Details
Published in:Computers & operations research Vol. 40; no. 1; pp. 498 - 509
Main Authors: Vincent, Thomas, Seipp, Florian, Ruzika, Stefan, Przybylski, Anthony, Gandibleux, Xavier
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.01.2013
Elsevier
Pergamon Press Inc
Subjects:
Algorithms
Applied sciences
Branch & bound algorithms
Branch and bound
Decision theory. Utility theory
Dominance filtering
Exact sciences and technology
Linear programming
Mathematical programming
Multi-objective linear programming
Multi-objective mixed integer programming
Multiple criteria decision making
Multiple objective
Nondominated set
Operational research and scientific management
Operational research. Management science
Operations research
Representations
Strategy
Studies
Nondominated set
Dominance filtering
Multi-objective mixed integer programming
Branch and bound
Multi-objective linear programming
Mixed programming
Branch and bound method
Multiobjective programming
Dominance
Linear programming
Mixed integer programming
Zero one programming
Filter
Implicit enumeration method
ISSN:0305-0548, 1873-765X, 0305-0548
Online Access:Get full text
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Summary:This work addresses the correction and improvement of Mavrotas and Diakoulaki's branch and bound algorithm for mixed 0-1 multiple objective linear programs. We first elaborate the issues encountered by the original algorithm and then propose a corrected version for the biobjective case using an exact representation of the nondominated set associated with an appropriate update procedure. Then we introduce several improvements using better bound sets and branching strategies and finally present some experiments to study the effectiveness of our propositions.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2012.08.003