A multi-product dynamic supply chain inventory model with supplier selection, joint replenishment, and transportation cost

José A. Ventura (), Boaz Golany (), Abraham Mendoza () and Chenxi Li ()
Additional contact information
José A. Ventura: The Pennsylvania State University
Boaz Golany: Technion—Israel Institute of Technology
Abraham Mendoza: Universidad Panamericana
Chenxi Li: The Pennsylvania State University

Annals of Operations Research, 2022, vol. 316, issue 2, No 2, 729-762

Abstract: Abstract The aim of this paper is to solve a multi-period supplier selection and inventory lot-sizing problem with multiple products in a serial supply chain. Compared to previous models proposed in the literature, our research incorporates a richer cost structure involving joint replenishment costs for raw material replenishment and production, and a more realistic description of the transportation costs represented as a vector of full-truck load costs for different size trucks. This problem can be displayed graphically as a time-expanded transshipment network defined by nodes and arcs that can be reached by feasible material flows. First, we propose an integrated mixed integer linear programming model that minimizes the cost over the entire supply chain for a given planning horizon. The model determines the optimal dynamic supplier selection, inventory lot-sizing, and production schedule simultaneously. Second, a sequential approach is proposed to solve the same problem. That is, a production schedule is determined first, and then a supplier selection and replenishment strategy is obtained according to that predetermined schedule. Sensitivity analysis comparing the two approaches is performed. Results show that, even though the integrated approach achieves the minimum cost, the sequential approach may be suitable for solving large-scale instances of the problem as it requires less information sharing and generates a near-optimal solution with shorter implementation time and computational effort.

Keywords: Supply chain management; Production planning; Multiple products; Time-varying demand; Supplier selection; Mixed integer linear programming (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-021-04508-z

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