An improved PSO algorithm for resource-constrained project scheduling problem

被引：0
|
作者：
Luo, Xinggang [1 ,2 ]
Wang, Dingwei [2 ]
Tang, Jianfu [2 ]
Tu, Yiliu [3 ]
机构：
[1] Northeastern Univ, Comp Ctr, Shenyang 110004, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China
[3] Univ Calgary, Dept Mechan & Mfg Engn, Calgary, AB, Canada
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
resource-constrained; project scheduling; particle swarm optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An improved Particle Swarm Optimization (PSO) algorithm for resource-con strained project scheduling problem is proposed. The particle presentation, encoding scheme and decoding rule of this algorithm are presented. Improvements based on the basic PSO include: the particle swarm is initialized by heuristic rule to improve the quality of particles; inertia weight is self-adapted with iteration of the algorithm to decelerate the speed of particles; crossover mechanism of genetic algorithm are applied to particle swarm to enable the exchange of good characteristics between two particles. Computational results for project instances of PSPLIB demonstrate that this improved PSO is effective compared with other mataheuristic approaches.
引用
收藏
页码：3514 / +
页数：2
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