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

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-leve...

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Bibliographic Details
Published in:Journal of control science and engineering 2015-01, Vol.2015 (2015), p.1-6
Main Authors: Zhang, Lieping, Zhang, Yu, Luo, Yingxiong
Format: Article
Language:English
Subjects:
Algorithms
Coding
Evolutionary algorithms
Libraries
Mathematical models
Optimization
Scheduling
Swarm intelligence
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Summary: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.
ISSN:1687-5249
1687-5257
DOI:10.1155/2015/923791