Abstract
In MOPSO (multiobjective particle swarm optimization), to maintain or increase the diversity of the swarm and help an algorithm to jump out of the local optimal solution, PAM (Partitioning Around Medoid) clustering algorithm and uniform design are respectively introduced to maintain the diversity of Pareto optimal solutions and the uniformity of the selected Pareto optimal solutions. In this paper, a novel algorithm, the multiobjective particle swarm optimization based on PAM and uniform design, is proposed. The differences between the proposed algorithm and the others lie in that PAM and uniform design are firstly introduced to MOPSO. The experimental results performing on several test problems illustrate that the proposed algorithm is efficient.
Highlights
Many real-world optimization problems often need to simultaneously optimize multiple objectives that are incommensurable and generally conflicting with each other
The main challenge for multiobjective evolutionary algorithms (MOEAs) is to be satisfied with three goals at the same time: (1) the Pareto optimal solutions are as near to true Pareto front, which means the convergence of MOEAs, (2) the nondominated solutions are evenly scattered along the Pareto front, which means the diversity of MOEAs, and (3) MOEAs obtain Pareto optimal solutions in limited evolution times [5]
This paper proposed a novel multiobjective particle swarm optimization based on PAM and uniform design, abbreviated as UKMOPSO
Summary
Many real-world optimization problems often need to simultaneously optimize multiple objectives that are incommensurable and generally conflicting with each other. They can usually be written as min. The particle swarm optimization algorithm, PSO, and MOEAs are both intelligent optimization algorithms It was proposed by Eberhart and Kennedy in 1995 [6, 7]. PAM is one of k-medoids clustering algorithms based on partitioning methods. It attempts to divide data objects into k partitions. This paper proposed a novel multiobjective particle swarm optimization based on PAM and uniform design, abbreviated as UKMOPSO.
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