A distributed co-evolutionary particle swarm optimization algorithm

被引：4
|
作者：
Liu, D. S. [1 ]
Tan, K. C. [1 ]
Ho, W. K. [1 ]
机构：
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore
来源：
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/CEC.2007.4424970
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper introduces a distributed co-evolutionary particle swarm optimization algorithm (DCPSO). In DCPSO, the population is decomposed into the subpopulations that are each responsible for optimizing one parameter, and co-evolve in a competitive manner. Such co-evolution mechanism with both cooperation and competition are designed to be effective and efficient in solving multi-objective (MO) problems wider distributed computation. The competition mechanism also indirectly helps DCPSO to overcome the fault-tolerance constraint in distributed computation. DCPSO shows substantial speedup from non-distributed version by sharing workload among computational nodes. In addition, a dynamic load balancing mechanism is used to further speed up the total runtime by minimizing the amount of idle time in each node.
引用
收藏
页码：3831 / 3838
页数：8
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