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

作     者：Zhang, Lieping Luo, Yingxiong Zhang, Yu 

作者机构：Guilin Univ Technol Guangxi Key Lab New Energy & Bldg Energy Saving Guilin 541004 Peoples R China Guilin Univ Technol Coll Mech & Control Engn Guilin 541004 Peoples R China Guilin Univ Technol Coll Informat Sci & Engn Guilin 541004 Peoples R China 

出 版 物：《JOURNAL OF CONTROL SCIENCE AND ENGINEERING》 (控制科学与工程学杂志)

年 卷 期：2015年第2015卷第10-5期

页      面：1-6页

核心收录：

学科分类：08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 

基　　金：Guangxi Natural Science Foundation [2014GXNSFAA118371] Guangxi Key Laboratory of New Energy and Building Energy Saving [12-03-21-3] 

主　　题：PARTICLE swarm optimization DIFFERENTIAL evolution (Computer science) PRODUCTION scheduling CODING theory PRODUCTION control 

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.