A reactive scheduling approach based on fuzzy inference for hybrid flowshop systems
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Date
2019
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Abstract
Hybrid flowshops consist of multiple production stages each of which has multiple parallel machines. Scheduling of hybrid flowshops is a NP-hard even in its simplest form. The presence of uncertainty in real-world problems forces the decision makers to reconsider their scheduling decisions in reactive manner. In this study, we proposed a proactive-reactive scheduling approach which allows to be changed dispatching rule set applied in time. The methodology consists of three parts: Shop Floor Management system with a triggering mechanism based on fuzzy inference system, performance prediction of the alternative dispatching rule sets based on Taguchi design, simulation, artificial neural networks, and a multi-criteria decision making methodology for determining new scheduling dispatching rule set. The proposed approach is applied on a real world problem from literature and the results are compared with static approach. © 2019 DAAAM International Vienna. All rights reserved.