Application of Hybrid Particle Swarm Optimization in Resource Constrained Multi-project Scheduling

作者：Du Hui^*; Lou Pei Huang; Ye Wen Hua

来源：Journal of the Chinese Society of Mechanical Engineers, 2014, 35(5): 371-379.

• Improved Particle Swarm Optimization (IPSO)
• Adaptive inertia weight
• Simulated Annealing (SA)
• Resource-Constrained Multi-project Scheduling (RCMPSP)

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.

• 出版日期2014-10
• 单位南京大学; 枣庄学院