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Disjunctive programming for multiobjective discrete optimisation

Disjunctive programming for multiobjective discrete optimisation
Disjunctive programming for multiobjective discrete optimisation
In this paper, I view and present the multiobjective discrete optimisation problem as a particular case of disjunctive programming where one seeks to identify efficient solutions from within a disjunction formed by a set of systems. The proposed approach lends itself to a simple yet effective iterative algorithm that is able to yield the set of all nondominated points, both supported and nonsupported, for a multiobjective discrete optimisation problem. Each iteration of the algorithm is a series of feasibility checks and requires only one formulation to be solved to optimality that has the same number of integer variables as that of the single objective formulation of the problem. The application of the algorithm show that it is particularly effective, and superior to the state-of-the-art, when solving constrained multiobjective discrete optimisation problem instances.
0899-1499
1-18
Bektas, Tolga
0db10084-e51c-41e5-a3c6-417e0d08dac9
Bektas, Tolga
0db10084-e51c-41e5-a3c6-417e0d08dac9

Bektas, Tolga (2018) Disjunctive programming for multiobjective discrete optimisation. INFORMS Journal on Computing, 1-18. (doi:10.1287/ijoc.2017.0804).

Record type: Article

Abstract

In this paper, I view and present the multiobjective discrete optimisation problem as a particular case of disjunctive programming where one seeks to identify efficient solutions from within a disjunction formed by a set of systems. The proposed approach lends itself to a simple yet effective iterative algorithm that is able to yield the set of all nondominated points, both supported and nonsupported, for a multiobjective discrete optimisation problem. Each iteration of the algorithm is a series of feasibility checks and requires only one formulation to be solved to optimality that has the same number of integer variables as that of the single objective formulation of the problem. The application of the algorithm show that it is particularly effective, and superior to the state-of-the-art, when solving constrained multiobjective discrete optimisation problem instances.

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Accepted/In Press date: 30 November 2017
e-pub ahead of print date: 2 November 2018
Published date: 2018

Identifiers

Local EPrints ID: 416359
URI: https://eprints.soton.ac.uk/id/eprint/416359
ISSN: 0899-1499
PURE UUID: 1daa0e43-39fb-4db0-97a6-6cd7b82ecb38
ORCID for Tolga Bektas: ORCID iD orcid.org/0000-0003-0634-144X

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Date deposited: 14 Dec 2017 17:30
Last modified: 14 Mar 2019 05:22

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