A comparative study of two key algorithms in multiple objective linear programming

Multiple objective linear programming problems are solved with a variety of algorithms. While these algorithms vary in philosophy and outlook, most of them fall into two broad categories: those that are decision space-based and those that are objective space-based. This paper reports the outcome of...

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Vydáno v:Journal of algorithms & computational technology Ročník 13
Hlavní autoři: Nyiam, Paschal B, Salhi, Abdellah
Médium: Journal Article
Jazyk:angličtina
Vydáno: London, England SAGE Publications 01.10.2019
Sage Publications Ltd
SAGE Publishing
Témata:
Algorithms
Comparative studies
Linear programming
Multiple objective analysis
Simplex method
outer-approximation algorithm
multiple criteria decision making
parametric simplex algorithm
most preferred nondominated point
Multiple objective linear programming
ISSN:1748-3018, 1748-3026
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Shrnutí:Multiple objective linear programming problems are solved with a variety of algorithms. While these algorithms vary in philosophy and outlook, most of them fall into two broad categories: those that are decision space-based and those that are objective space-based. This paper reports the outcome of a computational investigation of two key representative algorithms, one of each category, namely the parametric simplex algorithm which is a prominent representative of the former and the primal variant of Bensons Outer-approximation algorithm which is a prominent representative of the latter. The paper includes a procedure to compute the most preferred nondominated point which is an important feature in the implementation of these algorithms and their comparison. Computational and comparative results on problem instances ranging from small to medium and large are provided.
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ISSN:1748-3018
1748-3026
DOI:10.1177/1748302619870424