Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations

Tim Holzmann; J. C. Smith

doi:10.1016/j.ejor.2018.05.036

Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations

Tim Holzmann, J. C. Smith

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

Abstract

In this paper we present the modified augmented weighted Tchebychev norm, which can be used to generate a complete efficient set of solutions to a discrete multi-objective optimization problem. We contribute a generating algorithm that will, without supervision, generate the entire non-dominated set for any number of objectives. To our knowledge, this is the first generating method for general discrete multi-objective problems that uses a variant of the Tchebychev norm. In a computational study, our algorithm's running times are comparable to previously proposed algorithms.

Original language	English (US)
Pages (from-to)	436-449
Number of pages	14
Journal	European Journal of Operational Research
Volume	271
Issue number	2
DOIs	https://doi.org/10.1016/j.ejor.2018.05.036
State	Published - Dec 1 2018
Externally published	Yes

Keywords

Computational optimization
Generating methods
Multiple objective programming
Tchebychev norm

ASJC Scopus subject areas

General Computer Science
Modeling and Simulation
Management Science and Operations Research
Information Systems and Management

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10.1016/j.ejor.2018.05.036

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abstract = "In this paper we present the modified augmented weighted Tchebychev norm, which can be used to generate a complete efficient set of solutions to a discrete multi-objective optimization problem. We contribute a generating algorithm that will, without supervision, generate the entire non-dominated set for any number of objectives. To our knowledge, this is the first generating method for general discrete multi-objective problems that uses a variant of the Tchebychev norm. In a computational study, our algorithm's running times are comparable to previously proposed algorithms.",

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AB - In this paper we present the modified augmented weighted Tchebychev norm, which can be used to generate a complete efficient set of solutions to a discrete multi-objective optimization problem. We contribute a generating algorithm that will, without supervision, generate the entire non-dominated set for any number of objectives. To our knowledge, this is the first generating method for general discrete multi-objective problems that uses a variant of the Tchebychev norm. In a computational study, our algorithm's running times are comparable to previously proposed algorithms.

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KW - Generating methods

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Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations

Abstract

Keywords

ASJC Scopus subject areas

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