PSO for multi-objective problems: Criteria for leader selection and uniformity distribution | ||
| Journal of AI and Data Mining | ||
| مقاله 8، دوره 4، شماره 1، خرداد 2016، صفحه 67-76 اصل مقاله (719.75 K) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.5829/idosi.JAIDM.2016.04.01.08 | ||
| نویسنده | ||
| H. Motameni* | ||
| Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran. | ||
| چکیده | ||
| This paper proposes a method to solve multi-objective problems using improved Particle Swarm Optimization. We propose leader particles which guide other particles inside the problem domain. Two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. The first one is based on the mean of the m optimal particles and the second one is based on appointing a leader particle for any n founded particles. We used an intensity criterion to delete the particles in both techniques. The proposed techniques were evaluated based on three standard tests in multi-objective evolutionary optimization problems. The evaluation criterion in this paper is the number of particles in the optimal-Pareto set, error, and uniformity. The results show that the proposed method searches more number of optimal particles with higher intensity and less error in comparison with basic MOPSO and SIGMA and CMPSO and NSGA-II and microGA and PAES and can be used as proper techniques to solve multi-objective optimization problems. | ||
| کلیدواژهها | ||
| Multi-objective optimization؛ Particle Swarm Optimization؛ Intensity Distance؛ Mutation | ||
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