Solving resource availability cost problem in project scheduling by pseudo particle swarm optimization

被引：1

作者：

Jianjun Qi ^{[1
]}

Bo Guo ^{[1
]}

Hongtao Lei ^{[1
]}

Tao Zhang ^{[1
]}

机构：

[1] School of Information System and Management,National University of Defense Technology

来源：

Journal of Systems Engineering and Electronics | 2014年 / 25卷 / 01期

基金：

中国国家自然科学基金;

关键词：

project scheduling; resource availability cost problem(RACP); heuristics; particle swarm optimization(PSO); path relinking;

D O I：

暂无

中图分类号：

TP18 [人工智能理论]; O224 [最优化的数学理论];

学科分类号：

070105 ; 081104 ; 0812 ; 0835 ; 1201 ; 1405 ;

摘要：

This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish all activities before the deadline. There are finishstart type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of solving the resource availability cost problem(RACP) by using start time of each activity to code the schedule. Then, a novel heuristic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimization(PPSO) combined with PSO and path relinking procedure is presented to solve the RACP. Finally, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.

引用

页码：69 / 76

页数：8

共 24 条

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