Solving an Integration Process Planning and Scheduling in a Flexible Job Shop Using a Hybrid Approach

Abstract : Traditionally, process planning and scheduling functions are performed sequentially, where scheduling is implemented after process plans has been generated. Recent research works have shown that the integration of these two manufacturing system functions can significantly improve scheduling objectives. In this paper, we present a new hybrid method that integrates the two functions in order to minimize the makespan. This method is made up of a Shifting Bottleneck Heuristic as a starting solution, Tabu Search (TS) and the Kangaroo Algorithm metaheuristics as a global search. The performance of this newly hybrid method has been evaluated and compared with an integrated approach based on a Genetic Algorithm. Thereby, the characteristics and merits of the proposed method are highlighted.
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Nassima Keddari, Nasser Mebarki, Atif Shahzad, Zaki Sari. Solving an Integration Process Planning and Scheduling in a Flexible Job Shop Using a Hybrid Approach. 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA), May 2018, Oran, Algeria. pp.387-398, ⟨10.1007/978-3-319-89743-1_34⟩. ⟨hal-01913923⟩

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