A taboo search based approach to find the Pareto optimal set in multiple objective optimization

Baykasoglu A., Owen S., Gindy N.

ENGINEERING OPTIMIZATION, cilt.31, sa.6, ss.731-748, 1999 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31 Sayı: 6
  • Basım Tarihi: 1999
  • Doi Numarası: 10.1080/03052159908941394
  • Dergi Adı: ENGINEERING OPTIMIZATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.731-748
  • Anahtar Kelimeler: Pareto optimality, taboo search, multiple objective optimization, MULTIOBJECTIVE STRUCTURAL OPTIMIZATION, DISCRETE-CONTINUOUS VARIABLES, GENETIC ALGORITHMS, SINGLE
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

Taboo search is a heuristic optimization technique which works with a neighbourhood of solutions to optimize a given objective function. It is generally applied to single objective optimization problems. Taboo search has the potential for solving multiple objective optimization (MOO) problems, because it works with more than one solution at a time, and this gives it the opportunity to evaluate multiple objective functions simultaneously. In this paper, a taboo search based algorithm is developed to find Pareto optimal solutions in multiple objective optimization problems. The developed algorithm has been tested with a number of problems and compared with other techniques. Results obtained from this work have proved that a taboo search based algorithm can find Pareto optimal solutions in MOO effectively.