Stochastic inventory-routing problem with lateral transshipment for perishable product. (3rd June 2021)

• Record Type: Journal Article
• Authors: Fattahi, Parviz; Tanhatalab, Mehdi
• Is Part Of: Journal of modelling in management. Volume 17:Number 2(2022)
• Page Start: 539
• Page End: 568
• Publication Date: 2021-06-03
• Subjects: Optimization -- Inventory management -- Mathematical programming -- Inventory routing problem -- IRP -- Lagrangian relaxation -- Transshipment -- Chance-constrained programming; Industrial management -- Mathematical models -- Periodicals; Industrial management -- Computer simulation -- Periodicals; Business -- Mathematical models -- Periodicals; Business -- Computer simulation -- Periodicals; 658.4033
• DOI: 10.1108/JM2-09-2019-0230
• Languages: English
• ISSNs: 1746-5664

Abstract

Abstract : Purpose: This study aims to design a supply chain network in an uncertain environment while exists two options for distribution of the perishable product and production lot-sizing is concerned. Design/methodology/approach: Owing to the complexity of the mathematical model, a solution approach based on a Lagrangian relaxation (LR) heuristic is developed which provides good-quality upper and lower bounds. Findings: The model output is discussed through various examples. The introduction of some enhancements and using some heuristics results in better outputs in the solution procedure. Practical implications: This paper covers the modeling of some real-world problems in which demand is uncertain and managers face making some concurrent decisions related to supply chain management, transportation and logistics and inventory control issues. Furthermore, considering the perishability of product in modeling makes the problem more practically significant as these days there are many supply chains handling dairy and other fresh products. Originality/value: Considering uncertainty, production, transshipment and perishable product in the inventory-routing problem makes a new variant that has not yet been studied. The proposed novel solution is based on the LR approach that is enhanced by some heuristics and some valid inequalities that make it different from the current version of the LR used by other studies.