多级生产批量规划问题的柔性惯量反捕食粒子群算法-控制理论与应用.pdf

27 10 Vol. 27 No. 10 2010 10 Control Theory Applications Oct. 2010 :2010 , , , , (1. , 310023; 2. , 110819) : (MLLS)(MRP)(MPS), ; NP-hard. (APSO) (PSO) . (WAPSO) MLLS . 12benchmark1. (GA)Wagner-Whitin(WW). WAPSO . : ; ; ; ; : TP29 : A Anti-predatory particle-swarm optimization with flexible inertial weight for unconstrained multilevel lot-sizing problems HAN Yi , CAI Jian-hu , ZHOU Gen-gui , LI Yan-lai , TANG Jia-fu (1. College of Business Administration, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China; 2. Key Laboratory of Integrated Automation of Process Industry, Northeastern University, Shenyang Liaoning 110819, China) Abstract: Multilevel lot-sizing(MLLS) is a crucial problem in decision-making for the master production schedul- ing(MPP) of the material requirement plan(MRP), which is with broad industrial applications and has been considered the NP-hard combinatory optimization problem. Anti-predatory particle-swarm optimization(APSO), which is closely related to particle-swarm optimization(PSO), is a recently emerged meta-heuristics. An anti-predatory particle-swarm optimiza- tion with flexible inertial weight(WAPSO) is proposed to solve the unconstrained MLLS problem in a given assembly structure. A set of 12 small-sized benchmark data and a randomly generated medium size data are adopted to test the pro- posed algorithm. The experimental results are compared with those of genetic algorithm(GA) and Wagner-Whitin(WW) dynamic programming algorithm, the results show that WAPSO algorithm is an e