Abstract
Today’s complicated business environment has underscored the importance of integrated decision-making in supply chains. In this paper, a novel mixed-integer nonlinear mathematical model is proposed to integrate cellular manufacturing systems into a three-stage supply chain to deal with customers’ changing demands, which has been little explored in the literature. This model determines the types of vehicles to transport raw materials and final parts, the suppliers to procure, the priorities of parts to be processed, and the cell formation to configure work centers. In addition, queueing theory is used to formulate the uncertainties in demands, processing times, and transportation times in the model more realistically. A linearization method is employed to facilitate the tractability of the model. A genetic algorithm is also developed to deal with the NP-hardness of the problem. Numerous instances are used to validate the effectiveness of the modeling and the efficiency of solution procedures. Finally, a sensitivity analysis and a real case study are discussed to provide important management insights and evaluate the applicability of the proposed model.
Highlights
Today, the intensifying competitive pressures in the marketplace mean that companies must meticulously consider all stages of the production process, from the procurement of raw materials to the delivery of finished products, in order to survive
This paper addresses the advantage of considering Cellular manufacturing (CM) in the supply chain management under uncertainty
For large-scale test problems if Zave or Zbest is between Fbound and Fbest, it means that the proposed genetic algorithm (PGA) has obtained a better solution than the branch and bound (B&B) of Lingo software
Summary
Uncertainties throughout supply chain can relate to demand, shipping fleet transfer time, supplier delivery time, material handling time, operating time on machines in the factory and so on. This research aims to make an integrated decision throughout the supply chain under uncertainty owing to the expected reduction of costs in procurement, delay, material handling, and delivery; by adopting an integrated approach to decision-making, manufacturers can hope to gain a competitive edge To fulfill this purpose, the following three steps are considered simultaneously. Improvements in CF and cell management, reduce material handling time and resource consumption, respectively, which in turn affects delay cost This centralized decision improves the sustainability of decision considering demand, shipping fleet transfer time, and processing time under uncertainty.
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