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This research is to develop an approximate solution for a flow shop scheduling problem under the effects of fuzzy learning and deterioration with a common fuzzy due date by applying genetic algorithm technique. Real life is complex and filled with ambiguity and uncertainty. Due dates may not be always determined by a decision maker because of their biased approach and past experiences. Therefore, due dates may be defined in forms of any fuzzy set to encode decision makerâ€™s biased approaches and satisfaction levels for completion times of jobs. The objective function of the problem in this research is to maximise decision makerâ€™s sum of satisfaction levels with respect to completion times of jobs on a flow shop scheduling environment by applying genetic algorithm technique.
Keywords: Flow shop, fuzzy due date, genetic algorithm, learning effect, deterioration effect.
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