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Mathematics 2019, 7(2), 148; https://doi.org/10.3390/math7020148

A Multi-Objective Particle Swarm Optimization Algorithm Based on Gaussian Mutation and an Improved Learning Strategy

1,†
and
1,2,*,†
1
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China
2
Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Yinchuan 750021, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 8 January 2019 / Revised: 28 January 2019 / Accepted: 29 January 2019 / Published: 4 February 2019
(This article belongs to the Special Issue Evolutionary Algorithms in Intelligent Systems)
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Abstract

Obtaining high convergence and uniform distributions remains a major challenge in most metaheuristic multi-objective optimization problems. In this article, a novel multi-objective particle swarm optimization (PSO) algorithm is proposed based on Gaussian mutation and an improved learning strategy. The approach adopts a Gaussian mutation strategy to improve the uniformity of external archives and current populations. To improve the global optimal solution, different learning strategies are proposed for non-dominated and dominated solutions. An indicator is presented to measure the distribution width of the non-dominated solution set, which is produced by various algorithms. Experiments were performed using eight benchmark test functions. The results illustrate that the multi-objective improved PSO algorithm (MOIPSO) yields better convergence and distributions than the other two algorithms, and the distance width indicator is reasonable and effective. View Full-Text
Keywords: multi-objective optimization problems; particle swarm optimization (PSO); Gaussian mutation; improved learning strategy multi-objective optimization problems; particle swarm optimization (PSO); Gaussian mutation; improved learning strategy
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Sun, Y.; Gao, Y. A Multi-Objective Particle Swarm Optimization Algorithm Based on Gaussian Mutation and an Improved Learning Strategy. Mathematics 2019, 7, 148.

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