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

Tim Holzmann, J. C. Smith

Research output: Contribution to journalArticle

7 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 languageEnglish (US)
Pages (from-to)436-449
Number of pages14
JournalEuropean Journal of Operational Research
Volume271
Issue number2
DOIs
StatePublished - Dec 1 2018
Externally publishedYes

Keywords

  • Computational optimization
  • Generating methods
  • Multiple objective programming
  • Tchebychev norm

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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