An Analysis of the Inertia Weight Parameter for Binary Particle Swarm Optimization

作者: Jianhua Liu , Yi Mei , Xiaodong Li

DOI: 10.1109/TEVC.2015.2503422

关键词: Electronic mailContinuous optimizationKnapsack problemAccelerationConstant (mathematics)Mathematical optimizationInertiaBinary numberParticle swarm optimizationMathematics

摘要: In particle swarm optimization (PSO), the inertia weight is an important parameter for controlling its search capability. There have been intensive studies of in continuous optimization, but little attention has paid to binary case. This paper comprehensively investigates effect on performance PSO (BPSO), from both theoretical and empirical perspectives. A mathematical model proposed analyze behavior BPSO, based which several lemmas theorems are derived. Our research findings suggest that case, a smaller enhances exploration capability while larger encourages exploitation. Consequently, this proposes new adaptive scheme BPSO. allows process start first with gradually move toward exploitation by linearly increasing weight. The experimental results 0/1 knapsack problems show BPSO performs significantly better than conventional decreasing constant schemes. verifies efficacy

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