A territory defining multiobjective evolutionary algorithms and preference incorporation

Karahan I., Köksalan M.

IEEE Transactions on Evolutionary Computation, cilt.14, sa.4, ss.636-664, 2010 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 4
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1109/tevc.2009.2033586
  • Dergi Adı: IEEE Transactions on Evolutionary Computation
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.636-664
  • Anahtar Kelimeler: Crowding prevention, evolutionary algorithms, guidance, multiobjective optimization, preference incorporation
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

We have developed a steady-state elitist evolutionary algorithm to approximate the Pareto-optimal frontiers of multiobjective decision making problems. The algorithms define a territory around each individual to prevent crowding in any region. This maintains diversity while facilitating the fast execution of the algorithm. We conducted extensive experiments on a variety of test problems and demonstrated that our algorithm performs well against the leading multiobjective evolutionary algorithms. We also developed a mechanism to incorporate preference information in order to focus on the regions that are appealing to the decision maker. Our experiments show that the algorithm approximates the Pareto-optimal solutions in the desired region very well when we incorporate the preference information. © 2010 IEEE.