Job Shop Scheduling With Alternate Process Plan by Using Genetic Algorithm
نویسندگان
چکیده
Scheduling in a job-shop system is a challenging task, however it costly and time consuming. Successful implementation of automated manufacturing system highly depends on effective utilization of resource. Efficient scheduling algorithm for alternate process plan may increase the throughput rate, utilization of machine and guarantee a reasonable return of investment. In this paper, the objective is to prepare an alternate model with minimum makespan value by using genetic algorithm. For this makespan value to solve the various job sequencing problem, utilization of machine, cost of machine for a production shop that is characterized by alternate routing and flexible machines also investigates an optimization for scheduling job in a just-intime environment. All jobs can be processed through alternate routing to be processed in a specified order of operation. Each operation has to be processed on one of a set of resources (e.g. machine) with possibly different efficiency and hence processing time. The objective is to minimize the make span of the job, mean flow time, utilization of machine, Average utilization of machine.
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