A Novel Hybrid GA for the Assignment of Jobs to Machines in a Complex Hybrid Flow Shop Problem
This paper, investigates a complex manufacturing production system encountered in the food industry. We consider a two stage hybrid flow shop with two dedicated machines at stage1, and several identical parallel machines at stage 2. We consider two simultaneous constraints: the sequence dependent family setup times and time lags. The optimization criterion considered is the minimization of makespan. Given the complexity of problem, an hybrid genetic algorithms (HGA) based on an improving heuristic is presented. We experimented a new heuristic to assign jobs on the second stage. The proposed HGA is compared against a lower bound (LB), and against a mixed integer programming model (MIP). The results indicate that the proposed hybrid GA is effective and can produce near-optimal solutions in a reasonable amount of time.
KeywordsHybrid flow shop Sequence dependent family setup Hybrid genetic algorithm Time lag New heuristic Dedicated machine
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