Asynchronous Steady State Particle Swarm

被引：3
|
作者：
Fernandes, Carlos M. [1 ]
Julian Merelo, Juan [2 ]
Rosa, Agostinho C. [1 ]
机构：
[1] Univ Lisbon, LARSyS Lab Robot & Syst Engn & Sci, Lisbon, Portugal
[2] Univ Granada, Dept Comp Architecture, Granada, Spain
来源：
PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'16 COMPANION) | 2016年
关键词：
Particle Swarm Optimization; Asynchronous PSO; Self-Organized Criticality;
D O I：
10.1145/2908961.2909035
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We propose an asynchronous and steady state update strategy for the Particle Swarm Optimization inspired by the Bak-Sneppen model of co-evolution between interacting species: only the worst particle and its neighbors are updated and evaluated in each time-step. The strategy improves the quality of results and convergence speed of PSO with Moore neighborhood.
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页码：1 / 2
页数：2
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