A genetic algorithm approach to the scheduling of FMSs with multiple routes

Usually, most of the typical job shop scheduling approaches deal with the p rocessing 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 mac hines. This means that all parts, of all part types, can be processed throu gh alternative routings. Also, there can be several machines for each machi ne type. To solve these general scheduling problems, a genetic algorithm ap proach is proposed and the concepts of virtual and real operations are intr oduced. Chromosome coding and genetic operators of GAs are defined during t he 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.