Hybrid Particle Swarm and Differential Evolution Algorithm for Solving Multimode Resource-Constrained Project Scheduling Problem

被引：12
|
作者：
Zhang, Lieping [1 ,2 ]
Luo, Yingxiong [3 ]
Zhang, Yu [1 ,2 ]
机构：
[1] Guilin Univ Technol, Guangxi Key Lab New Energy & Bldg Energy Saving, Guilin 541004, Peoples R China
[2] Guilin Univ Technol, Coll Mech & Control Engn, Guilin 541004, Peoples R China
[3] Guilin Univ Technol, Coll Informat Sci & Engn, Guilin 541004, Peoples R China
来源：
JOURNAL OF CONTROL SCIENCE AND ENGINEERING | 2015年 / 2015卷
关键词：
D O I：
10.1155/2015/923791
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to find a feasible solution for the multimode resource-constrained project scheduling problem (MRCPSP), a hybrid of particle swarm optimization (PSO) and differential evolution (DE) algorithm is proposed in this paper. The proposed algorithm uses a two-level coding structure. The upper-level structure is coded for scheduling sequence, which is optimized by PSO algorithm. The lower-level structure is coded for project execution mode, and DE algorithm is used to solve the optimal scheduling model. The effectiveness and advantages of the proposed algorithm are illustrated by using the test function of project scheduling problem library (PSPLIB) and comparing with other scheduling methods. The results show that the proposed algorithm can well solve MRCPSP.
引用
收藏
页数：6
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