文章基本信息

标题：Solving Path Planning Problem Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights
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作者：Yi-Xuan Lu ; Jie-Sheng Wang ; Sha-Sha Guo 等
期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2019
卷号：46
期号：4
页码：628-636
出版社：IAENG - International Association of Engineers
摘要：The path planning problem refers to find theshortest path to reach the predetermined target position in acertain complex environment. Particle swarm optimization(PSO) algorithm is derived from the imitation of the populationcooperation of the flock and the predatory behavior of thecompetition. The sharing of information by the individuals inthe swarm makes the movement of the whole swarm in theproblem solution space from disorder process to order process.In this paper, the improved PSO algorithm based on improvedinertia weights is adopted to solve the path planning problems.For the three constructed different maps, the improved PSOalgorithm based on five different inertia weight adjustmentstrategies is used to solve the path planning problems. Thesimulation results are used to verify the effectiveness of theproposed algorithm and inertia weight adjustment strategies.
关键词：path planning problem; particle swarm;optimization algorithm; inertia weight