On the simplex, interior-point and objective space approaches to multiobjective linear programming

Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point method of Linear Programming. However, objective space based methods are becoming more and more prominent. This paper investigates three algorithm...

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Published in:Journal of algorithms & computational technology Vol. 15
Main Authors: Nyiam, Paschal B, Salhi, Abdellah
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.10.2021
Sage Publications Ltd
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ISSN:1748-3018, 1748-3026
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Abstract Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point method of Linear Programming. However, objective space based methods are becoming more and more prominent. This paper investigates three algorithms namely the Extended Multiobjective Simplex Algorithm (EMSA), Arbel’s Affine Scaling Interior-point (ASIMOLP) algorithm and Benson’s objective space Outer Approximation (BOA) algorithm. An extensive review of these algorithms is also included. Numerical results on non-trivial MOLP problems show that EMSA and BOA are at par and superior in terms of the quality of a most preferred nondominated point to ASIMOLP. However, ASIMOLP more than holds its own in terms of computing efficiency.
AbstractList Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point method of Linear Programming. However, objective space based methods are becoming more and more prominent. This paper investigates three algorithms namely the Extended Multiobjective Simplex Algorithm (EMSA), Arbel’s Affine Scaling Interior-point (ASIMOLP) algorithm and Benson’s objective space Outer Approximation (BOA) algorithm. An extensive review of these algorithms is also included. Numerical results on non-trivial MOLP problems show that EMSA and BOA are at par and superior in terms of the quality of a most preferred nondominated point to ASIMOLP. However, ASIMOLP more than holds its own in terms of computing efficiency.
Author Nyiam, Paschal B
Salhi, Abdellah
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  givenname: Abdellah
  surname: Salhi
  fullname: Salhi, Abdellah
  organization: Department of Mathematical Sciences, University of Essex, Colchester, UK
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Keywords affine scaling interior MOLP algorithm
outer-approximation algorithm
multiobjective simplex algorithm
most preferred nondominated point
Multiple objective linear programming
Language English
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Snippet Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point...
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SubjectTerms Algorithms
Linear programming
Mathematical analysis
Multiple objective analysis
Simplex method
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Title On the simplex, interior-point and objective space approaches to multiobjective linear programming
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