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Journal of Control Science and Engineering
Volume 2015 (2015), Article ID 923791, 6 pages
http://dx.doi.org/10.1155/2015/923791
Research Article

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

1Guangxi Key Laboratory of New Energy and Building Energy Saving, Guilin University of Technology, Guilin 541004, China
2College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541004, China
3College of Information Science and Engineering, Guilin University of Technology, Guilin 541004, China

Received 14 July 2015; Revised 11 September 2015; Accepted 14 September 2015

Academic Editor: Petko Petkov

Copyright © 2015 Lieping Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.