A Genetic Algorithm Approach to the Scheduling of FMSs with Multiple Routes

Usually, most of the typical job shop scheduling approaches deal with the processing sequence of parts in a fixed routing condition. In this paper, we suggest a genetic algorithm (GA) to solve the job-sequencing problem for a production shop that is characterized by flexible routing and flexible machines. This means that all parts, of all part types, can be processed through alternative routings. Also, there can be several machines for each machine type. To solve these general scheduling problems, a genetic algorithm approach is proposed and the concepts of virtual and real operations are introduced. Chromosome coding and genetic operators of GAs are defined during the problem solving. A minimum weighted tardiness objective function is used to define code fitness, which is used for selecting species and producing a new generation of codes. Finally, several experimental results are given.

[1]  Subhash Wadhwa,et al.  Impact of Routing Flexibility on the Performance of an FMS—A Simulation Study , 1997 .

[2]  Jacek Blazewicz,et al.  The job shop scheduling problem: Conventional and new solution techniques , 1996 .

[3]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  Lawrence Davis,et al.  Job Shop Scheduling with Genetic Algorithms , 1985, ICGA.

[6]  Erwin Pesch,et al.  Evolution based learning in a job shop scheduling environment , 1995, Comput. Oper. Res..

[7]  C. Bierwirth.  A generalized permutation approach to job shop scheduling with genetic algorithms , 1995 .

[8]  John E. Biegel,et al.  Genetic algorithms and job shop scheduling , 1990 .

[9]  Takeshi Yamada,et al.  Conventional Genetic Algorithm for Job Shop Problems , 1991, ICGA.

[10]  Gunar E. Liepins,et al.  Genetic algorithms: Foundations and applications , 1990 .

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  Frank DiCesare,et al.  Scheduling flexible manufacturing systems using Petri nets and heuristic search , 1994, IEEE Trans. Robotics Autom..

[13]  Emanuel Falkenauer,et al.  A genetic algorithm for job shop , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[14]  Krishna R. Pattipati,et al.  A practical approach to job-shop scheduling problems , 1993, IEEE Trans. Robotics Autom..

[15]  FEDERICO DELLA CROCE,et al.  A genetic algorithm for the job shop problem , 1995, Comput. Oper. Res..