东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (12): 1681-1684.DOI: -

• 论著 • 上一篇    下一篇

基于OpenMP求解无容量设施选址问题的并行PSO算法

王大志;闫杨;汪定伟;王洪峰;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-12-15 发布日期:2013-06-22
  • 通讯作者: Wang, D.-Z.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金重点项目(70431003);;国家创新研究群体科学基金资助项目(60521003);;国家科技支撑计划项目(2006BAH02A09)

OpenMP-based multi-population PSO algorithm to solve the uncapacitated facility location problem

Wang, Da-Zhi (1); Yan, Yang (1); Wang, Ding-Wei (1); Wang, Hong-Feng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-12-15 Published:2013-06-22
  • Contact: Wang, D.-Z.
  • About author:-
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摘要： 讨论无容量设施选址(UFL)问题,提出了一个基于OpenMP技术的并行多粒子群优化(PSO)算法.将整个种群分为若干子种群,同时利用局部信息来更新粒子速度,使得并行算法异步进行.算法运行一定代数后,每个子种群都会与其相邻种群交换最优粒子.通过将并行多粒子群算法对OR-library中的标准测试问题进行测试,并将计算结果与串行多粒子群算法的计算结果进行比较.相比之下,并行多粒子群算法执行时间短,特别对于大规模的计算问题,所得结果有更好的鲁棒性.

关键词: 粒子群算法, 无容量设施选址问题, 并行计算, OpenMP, 多种群

Abstract: The OpenMP-based parallel multi-population particle swarm optimization (PSO) algorithm to solve the incapacitated facility location (UFL) problem. The parallel algorithm is operating asynchronously by dividing the whole particle swarm into several sub-swarm and the particle velocity is updated with a variety of local optima. Every sub-swarm exchange its optimal particle with its neighboring swarm after the algorithm operated for a certain number of generations The parallel multi-population PSO (PMPSO) algorithm is applied to several benchmark suits collected from OR-library, and the results are compared to that of the serial multi-population PSO. It is found that the parallel multi-population PSO is time saving in execution, especially in the large scale computation it will provide higher robustness.

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