The Research of Parallel Multi-objective Particle Swarm Optimization Algorithm

被引：0
|
作者：
Wu Jian
Tang XinHua
Cao Yong
机构：
[1] Shandong Univ Polit Sci & Law, Key Lab Evidence Identifying Univ Shandong, Jinan 250014, Shandong, Peoples R China
[2] Shandong Univ Polit Sci & Law, Dept Informat Sci & Technol, Jinan 250014, Shandong, Peoples R China
来源：
2014 5TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS) | 2014年
关键词：
particle swarm algorithm; parallel; multi-objective optimization;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The shortcomings of traditional serial algorithm on the multi-objective optimization problems are well known for its long computation time and the slow convergence rate, especially when we have complicated computation and large amount of data. To conquer these shortcomings, we propose a parallel multi-objective particle swarm optimization algorithm. Through analyzing the mechanism of multi-objective particle swarm optimization algorithm, we introduced the parallel mechanism into the multi-objective particle swarm algorithm, and realized a parallel multi-objective particle swarm algorithm based on the model of the island. We apply our algorithm on the knapsack problem as an illustration, and find the solving efficiency of the multi-objective problems improves evidently.
引用
收藏
页码：300 / 304
页数：5
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