Exploiting tabu search memory in constrained problems

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

Research output: Contribution to journalArticlepeer-review

48 Scopus citations


This paper puts forth a general method to optimize constrained problems effectively when using tabu search. An adaptive penalty approach is used that exploits the short-term memory structure of the tabu list along with the long-term memory of the search results. It is shown to be effective on a variety of combinatorial problems with different degrees and numbers of constraints. The approach requires few parameters, is robust to their setting, and encourages search in promising regions of the feasible and infeasible regions before converging to a final feasible solution. The method is tested on three diverse NP-hard problems, facility layout, system reliability optimization, and orienteering, and is compared with two other penalty approaches developed explicitly for tabu search. The proposed memory-based approach shows consistent strong performance.

Original languageEnglish (US)
Pages (from-to)241-254
Number of pages14
JournalINFORMS Journal on Computing
Issue number3
StatePublished - 2004

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research


Dive into the research topics of 'Exploiting tabu search memory in constrained problems'. Together they form a unique fingerprint.

Cite this