首页|期刊导航|东华大学学报（英文版）|A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time
东华大学学报（英文版）2008，Vol.25Issue(2)：115-122,8.
A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time
A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time
摘要
Abstract
Since in most practical cases the processing time of scheduling is not deterministic,flow shop scheduling model with fuzzy processing time is established.It is assumed that the processing times of jobs on the machines are described by triangular fuzzy sets.In order to find a sequence that minimizes the mean makespan and the spread of the makespan,Lee and Li fuzzy ranking method is adopted and modified to solve the problem.Particle swarm optimization (PSO) is a population-based stochyastic appmxilmtion aigorithm that has been applied to a wide range of problems,but there is little reported in respect of application to scheduling problems because of its unsuitability for them.In the paper,PSO is redefined and modified by introducing genetic operations such as crossover and mutation to update the particles,which is called GPSO and successfully employed to solve the formulated problem.A series of benchmarks with fuzzy processing time are used to verify GPSO.Extensive experiments show the feasibility and effectiveness of the proposed method.关键词
flow shop/scheduling/fuzzy/PSOKey words
flow shop/scheduling/fuzzy/PSO分类
信息技术与安全科学引用本文复制引用
NIU Qun,GU Xing-sheng..A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time[J].东华大学学报（英文版）,2008,25(2):115-122,8.基金项目
Supported by The National Natural Science Foundation of China(No.60774078),Innovation Foundation of Shanghai University,Scientific Research Special Fund of Shanghai Excellent Young Teachers,Chenguang Project (No.2008 CG48) and Shanghai Leading Academic Discipline Project(No.T0103) （No.60774078）
