DOPGA: a new fitness assignment scheme for multi-objective evolutionary algorithms
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, cilt.45, sa.3, ss.407-426, 2014 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 45 Sayı: 3
- Basım Tarihi: 2014
- Doi Numarası: 10.1080/00207721.2012.724095
- Dergi Adı: INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.407-426
- Anahtar Kelimeler: fitness assignment, domination power, DOPGA, evolutionary algorithms, SPEA and SPEA2, test functions, NSGA-II, OPTIMIZATION
- Ondokuz Mayıs Üniversitesi Adresli: Evet
Özet
In this article, a new fitness assignment scheme to evaluate the Pareto-optimal solutions for multi-objective evolutionary algorithms is proposed. The proposed DOmination Power of an individual Genetic Algorithm (DOPGA) method can order the individuals in a form in which each individual (the so-called solution) could have a unique rank. With this new method, a multi-objective problem can be treated as if it were a single-objective problem without drastically deviating from the Pareto definition. In DOPGA, relative position of a solution is embedded into the fitness assignment procedures. We compare the performance of the algorithm with two benchmark evolutionary algorithms (Strength Pareto Evolutionary Algorithm (SPEA) and Strength Pareto Evolutionary Algorithm 2 (SPEA2)) on 12 unconstrained bi-objective and one tri-objective test problems. DOPGA significantly outperforms SPEA on all test problems. DOPGA performs better than SPEA2 in terms of convergence metric on all test problems. Also, Pareto-optimal solutions found by DOPGA spread better than SPEA2 on eight of 13 test problems.