Fitness estimation and the particle swarm optimisation algorithm

被引:16
|
作者
Hendtlass, Tim [1 ]
机构
[1] Swinburne Univ Technol, Ctr Informat Technol Res, Hawthorn, Vic 3122, Australia
关键词
D O I
10.1109/CEC.2007.4425028
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The time taken performing fitness calculations can dominate the total computational time when applying Particle Swarm Optimisation (PSO) to complex real life problems. This paper describes a method of estimating fitness, and the reliability of that estimation, that can be used as an alternative to performing some true fitness calculations. The fitness estimation is always made, but, should the reliability of this fitness estimation drop below a user specified threshold, the estimate is discarded and a true fitness evaluation performed. Results are presented for three problems that show that the number of true fitness evaluations can be significantly reduced by this method without degrading the performance of PSO. Further the value used for the threshold, the only new parameter introduced, is shown not to be sensitive, at least on these test problems. Provided that the time to perform a true fitness evaluation is far longer than the time for the fitness and reliability calculations, a substantial amount of computing time can be saved while still achieving the same end result.
引用
收藏
页码:4266 / 4272
页数:7
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