Multi-objective tabu search using a multinomial probability mass function

Sadan Kulturel-Konak, Alice E. Smith, Bryan A. Norman

Research output: Contribution to journalArticle

53 Citations (Scopus)

Abstract

A tabu search approach to solve multi-objective combinatorial optimization problems is developed in this paper. This procedure selects an objective to become active for a given iteration with a multinomial probability mass function. The selection step eliminates two major problems of simple multi-objective methods, a priori weighting and scaling of objectives. Comparison of results on an NP-hard combinatorial problem with a previously published multi-objective tabu search approach and with a deterministic version of this approach shows that the multinomial approach is effective, tractable and flexible.

Original languageEnglish (US)
Pages (from-to)918-931
Number of pages14
JournalEuropean Journal of Operational Research
Volume169
Issue number3
DOIs
StatePublished - Mar 16 2006

Fingerprint

Tabu search
Tabu Search
Multiobjective Combinatorial Optimization
Combinatorial optimization
Multiobjective Optimization Problems
Combinatorial Problems
NP-hard Problems
Combinatorial Optimization Problem
Weighting
Eliminate
Scaling
Iteration

All Science Journal Classification (ASJC) codes

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

Cite this

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Multi-objective tabu search using a multinomial probability mass function. / Kulturel-Konak, Sadan; Smith, Alice E.; Norman, Bryan A.

In: European Journal of Operational Research, Vol. 169, No. 3, 16.03.2006, p. 918-931.

Research output: Contribution to journalArticle

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