A two-stage stochastic supply chain scheduling problem with production in cellular manufacturing environment: A case study

Document Type : Article

Authors

Department of Industrial Engineering, Iran University of Science and Technology, University Ave. Narmak, Tehran, P.O. Box 1684613114, Iran

Abstract

An integrated decision in supply chain is a significant principle in order to compete in today’s market. This paper proposes a novel mathematical model in a two-stage supply chain scheduling to cooperate procurement and manufacturing activities. The supply chain scheduling along with the production approach of cellular manufacturing under demand, processing time, and transportation time uncertainties makes business environment sustainably responsive to the changing needs of customers. Uncertainties are formulated by queuing theory. In this paper, a new mixed-integer nonlinear programming formulation is used to determine types of vehicles to carry raw materials, suppliers to procure, priority of each part in order to process, and cell formation to configure work centers. The goal is to minimize total tardiness. A linearization method is used to ease tractability of the model. A genetic algorithm is developed due to the NP-hard nature of the problem. The parameters of the genetic algorithm are set and estimated by Taguchi’s experimental design. Numerous test problems are employed to validate the effectiveness of the modeling and the efficiency of solution approaches. Finally, a real case study and a sensitivity analysis are discussed to provide significant managerial insights and assess the applicability of the proposed model.

Keywords


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Volume 30, Issue 4 - Serial Number 4
Transactions on Industrial Engineering (E)
July and August 2023
Pages 1399-1422
  • Receive Date: 09 May 2019
  • Revise Date: 30 March 2021
  • Accept Date: 05 July 2021