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Paper Information

Journal:   PRODUCTION AND OPERATIONS MANAGEMENT   fall 2018-winter 2019 , Volume 9 , Number 2 (17) ; Page(s) 1 To 22.

Multi-Objective Hybrid Metaheuristic Search Algorithm for Distributed Reentrant Permutation Flow Shop Scheduling Via Considering Preventive Maintenance under Uncertainty

* Department of Industrial Engieering and Management, Shahrood University of Technology, Shahrood, Iran
Distributing the production activities among the supply chain facilities with regard to the considered criteria can have a significant impact on the productive management. In this paper, a comprehensive mathematical model for reentrant permutation flow shop scheduling via considering a preventive maintenance and distributed jobs on different facilities is proposed. The uncertainty of the time of preventive maintenance operation is handled using robust optimization technique based on the uncertainty budget approach. Job assignment to production facilities and job scheduling are determined in the proposed model by considering multiple objectives include Cmax minimization, production cost minimization, and average tardiness. Due to the NP-hard nature of the proposed flow shop scheduling problem, a new hybrid meta-heuristic based on the novel adaptive large neighborhood search and the simulated annealing is adopted. The obtained results from an extensive numerical experimentation indicate the efficiency of the proposed model and solution algorithm to tackle the proposed problem.
Keyword(s): Distributed Scheduling,Reentrant Permutation Flow Shop,Preventive Maintenance,Uncertainty,Hybrid,Metaheuristic Algorithm
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