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Sequencing Mixed-model Production Systems by Modified Multi-objective Genetic Algorithms 被引量:5

Sequencing Mixed-model Production Systems by Modified Multi-objective Genetic Algorithms
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摘要 As two independent problems,scheduling for parts fabrication line and sequencing for mixed-model assembly line have been addressed respectively by many researchers.However,these two problems should be considered simultaneously to improve the efficiency of the whole fabrication/assembly systems.By far,little research effort is devoted to sequencing problems for mixed-model fabrication/assembly systems.This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line with limited intermediate buffers and two flexible parts fabrication flow lines with identical parallel machines and limited intermediate buffers.Two objectives are considered simultaneously:minimizing the total variation in parts consumption in the assembly line and minimizing the total makespan cost in the fabrication/assembly system.The integrated optimization framework,mathematical models and the method to construct the complete schedules for the fabrication lines according to the production sequences for the first stage in fabrication lines are presented.Since the above problems are non-deterministic polynomial-hard(NP-hard),a modified multi-objective genetic algorithm is proposed for solving the models,in which a method to generate the production sequences for the fabrication lines from the production sequences for the assembly line and a method to generate the initial population are put forward,new selection,crossover and mutation operators are designed,and Pareto ranking method and sharing function method are employed to evaluate the individuals' fitness.The feasibility and efficiency of the multi-objective genetic algorithm is shown by computational comparison with a multi-objective simulated annealing algorithm.The sequencing problems for mixed-model production systems can be solved effectively by the proposed modified multi-objective genetic algorithm. As two independent problems,scheduling for parts fabrication line and sequencing for mixed-model assembly line have been addressed respectively by many researchers.However,these two problems should be considered simultaneously to improve the efficiency of the whole fabrication/assembly systems.By far,little research effort is devoted to sequencing problems for mixed-model fabrication/assembly systems.This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line with limited intermediate buffers and two flexible parts fabrication flow lines with identical parallel machines and limited intermediate buffers.Two objectives are considered simultaneously:minimizing the total variation in parts consumption in the assembly line and minimizing the total makespan cost in the fabrication/assembly system.The integrated optimization framework,mathematical models and the method to construct the complete schedules for the fabrication lines according to the production sequences for the first stage in fabrication lines are presented.Since the above problems are non-deterministic polynomial-hard(NP-hard),a modified multi-objective genetic algorithm is proposed for solving the models,in which a method to generate the production sequences for the fabrication lines from the production sequences for the assembly line and a method to generate the initial population are put forward,new selection,crossover and mutation operators are designed,and Pareto ranking method and sharing function method are employed to evaluate the individuals' fitness.The feasibility and efficiency of the multi-objective genetic algorithm is shown by computational comparison with a multi-objective simulated annealing algorithm.The sequencing problems for mixed-model production systems can be solved effectively by the proposed modified multi-objective genetic algorithm.
作者 WANG Binggang
出处 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2010年第5期537-546,共10页 中国机械工程学报(英文版)
基金 supported by National Natural Science Foundation of China (Grant No.50875101) National Hi-tech Research and Development Program of China (863 Program,Grant No.2007AA04Z186)
关键词 mixed-model production system SEQUENCING parallel machine BUFFERS multi-objective genetic algorithm multi-objective simulated annealing algorithm mixed-model production system sequencing parallel machine buffers multi-objective genetic algorithm multi-objective simulated annealing algorithm
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  • 1FRY T D, OLIFF M D, MINOR E D, et al. The effect of product structure and sequencing rule on assembly shop performance[J]. International Journal of Production Research, 1989, 27(4): 671-686.
  • 2HUAN P Y. A comparative study of priority dispatching roles in a hybrid assembly/job shop[J]. International Journal of Production Research, 1984, 22(3): 375-387.
  • 3PHILIPOON P R, RUSSEL R S, FRY T D. A preliminary investigation of multi-attribute based sequencing rules for assembly shops[J]. International Journal of Production Research, 1991, 29(4): 739-753.
  • 4DOCTOR S R, CAVALIER T M, EGBELU P J. Scheduling for machining and assembly in a job-shop environment[J]. International Journal of Production Research, 1993, 31(6): 1 275-1 297.
  • 5MCKOY D H C, EGBELU P J. Minimizing production flow time in a process and assembly job shop[J]. International Journal of Production Research 1998 31(8): 2 315-2 332.
  • 6CHENG T C E. Analysis of material flow in a job shop with assembly operations[J]. International Journal of Production Research, 1990, 28(7): 1 369-1 383.
  • 7THIAGARAJAN S, RAJENDRAN C. Scheduling in dynamic assembly job-shops having different holding and tardiness costs[J]. International Journal of Production Research, 2003, 41(18): 4 453- 4 486.
  • 8THIAGARAJAN S, RAJENDRAN C. Scheduling in dynamic assembly job-shops to minimize the sum of weighted earliness, weighted tardiness and weighted flowtime of jobs[J]. Computers and Industrial Engineering, 2005, 49(4): 463-503.
  • 9GAAFAR L K, MASOUD S A. Genetic algorithms and simulated annealing for scheduling in agile manufacturing[J]. International Journal of Production Research, 2005, 43(14): 3 069-3 085.
  • 10LEE C Y, CHENG T C E, LIN B M T. Minimizing the makespan in the 3-machine assembly-type flowshop scheduling problem[J]. Management Science, 1993, 39(5): 616-625.

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