Application of hybrid particle swarm optimization in resource constrained multi-project scheduling

被引：0

作者：

Du, Hui ^{[1
,2
]}

Lou, Pei-Huang ^{[3
]}

Ye, Wen-Hua ^{[3
]}

机构：

[1] Zaozhuang University, Zaozhuang,277160, China

[2] Nanjing University of Aeronautics & Astronautics, Nanjing,210016, China

[3] Department of Mechanical Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing,210016, China

来源：

Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao | 2014年 / 35卷 / 05期

关键词：

Scheduling - Constrained optimization - Particle swarm optimization (PSO);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The Resource Constrained Multi-project Scheduling Problem (RCMPSP) is a NP-hard optimization problem, which is hard to be solved effectively by using single algorithm. This paper presents a hybrid algorithm based on Improved Particle Swarm Optimization and Simulated Annealing (IPSOSA) algorithm to solve the RCMPSP. Aimed at overcoming the shortcomings of premature convergence of standard PSO, adaptive inertia weight with cyclical attenuation strategy and Simulated Annealing algorithm (SA) are employed in the hybrid algorithm. The proposed IPSOSA was applied to aircraft assembly tooling manufacturing, and we compare the result of the IPSOSA with the results of GA, SA and standard PSO methods. The simulation results and algorithm comparison show that the IPSOSA algorithm is an effective approach for the RCMPSP. © 2014, Chinese Mechanical Engineering Society. All right reserved.

引用

页码：371 / 379