MINIMIZATION FLOW TIME IN FLEXIBLE DYNAMIC JOB SHOP SCHEDULING PROBLEM WITH PARALLEL MACHINES

In this paper, we investigate flexible job-shop scheduling with parallel machines in the dynamic manufacturing environment (FDJSPM). In this study, moreover, considering a dynamic manufacturing environment (causing interval jobs in non-zero time), it contains two kinds of flexibility. Flexibility in the scheduling problems is effective for improving operational manufacturing systems. Non-flexibility leads to scheduling programs that have problems, like useless loading machines, bottleneck machines, decreased desirability sources and poor functioning of just in time delivery. Flexibility arising from parallel machines is a special expression of operation flexibility. In this statement, there are one or several identical machines (PM). Regarding the mentioned flexibility in manufacturing systems, a job could be processed, not only in several stations (operational flexibility), but, also, on several parallel machines in each station (flexibility of parallel machines).
In the present research, the noted scheduling objective is concluded mean flow time. Since the problem is NP-hard, a Genetic Algorithm was applied in salvation. So, the operational proposed GA is compared with a similar approach in the literature (RKGA), where the results demonstrate the inherence of the proposed GA.