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A Genetic Algorithm Approach for Process Planning and Scheduling in Job Shop Environment

Traditionally, scheduling and process planning are considered as two different functions in a manufacturing environment. In this paper we consider the simultaneous selection of best process plan and scheduling of jobs in a job shop environment. We propose a spreadsheet based genetic algorithm (GA) to solve this class of problem. The shop model is built in Microsoft Excel spreadsheet to find the optimized process plan and corresponding schedule. Benchmark problems already published in the literature have been taken to demonstrate the performance of the proposed algorithm. Results obtained from proposed approach are equal or better than the earlier studies. It is also shown that the proposed algorithm is general purpose and could be used to optimize any objective function without changing the model or the GA routine.