Particle Swarm Optimization Combined with Tabu Search in a Multi-agent Model for Flexible Job Shop Problem
Flexible job shop scheduling problem (FJSP) is an important exten sion of the classical job shop scheduling problem, where the same operation could be processed on more than one machine and has a processing time de pending on the machine used.The objective is to minimize the makespan, i.e.,the total duration of the schedule.In this article, we propose a multi-agent mod el based on the hybridization of the tabu search (TS) method and particle swarm optimization (PSO) in order to solve FJSP.Different techniques of diversifica tion have also been explored in order to improve the performance of our model.Our approach has been tested on a set of benchmarks existing in the literature.The results obtained show that the hybridization of TS and PSO led to promising results.
Flexible Job Shop Multi-agent system Tabu Search Particle swarm optimization Diversification techniques
Abir Henchiri Meriem Ennigrou
ISG, Institut Supérieur de Gestion, ur.SOIE, Stratégies dOptimisation et Informatique Intelligente, 2000 Le Bardo, Tunisia
国际会议
4th international Conference,ICSI2013(第4届群体智能国际会议)
哈尔滨
英文
385-394
2013-06-12（万方平台首次上网日期，不代表论文的发表时间）