Hybrid Particle Swarm and Differential Evolution Algorithm for Solving Multimode Resource-Constrained Project Scheduling Problem. (5th October 2015)

• Record Type: Journal Article
• Authors: Zhang, Lieping; Luo, Yingxiong; Zhang, Yu
• Other Names: Petkov Petko Academic Editor.
• Is Part Of: Journal of control science and engineering. Volume 2015(2015)
• Publication Date: 2015-10-05
• Subjects: Control theory -- Periodicals; 629.831205
• DOI: 10.1155/2015/923791
• Languages: English
• ISSNs: 1687-5249

Abstract

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.