Bi-objective optimisation of the joint replenishment problem in a two-echelon supply chain

Pejman Ahmadi, Seyed Hamid Reza Pasandideh, Leopoldo Eduardo Cárdenas-Barrón () and Seyed Taghi Akhavan Niaki

International Journal of Services and Operations Management, 2021, vol. 38, issue 3, 336-359

Abstract: In this research, a bi-objective optimisation model for the joint replenishment problem (JRP) of a supply chain comprised of a single supplier and multiple retailers is developed, in which the retailers are assumed to be members of a unique distribution company. The mathematical model minimises the supplier's as well as the retailers' cost subject to some constraints. The constraints are the required storage spaces for any retailer, for any product, and for all the products. The benefit of using the JRP policy is shown based on minimising total cost of supplier and retailers. Since the developed model of the problem is NP-hard, the multi-objective meta-heuristic optimisation algorithm of non-dominated sorting genetic algorithm-II (NSGA-II) is proposed to solve the problem. Besides, since no benchmark is available in the literature to verify and validate the results obtained, a non-dominated ranking genetic algorithm (NRGA) is suggested to solve the problem as well. For further validation, the Pareto fronts are compared to lower and upper bounds obtained using a genetic algorithm employed to solve two single-objective problems separately.

Keywords: supply chain management; joint replenishment problem; JRP; non-dominated sorting genetic algorithm-II; NSGA-II; non-dominated ranking genetic algorithm; NRGA. (search for similar items in EconPapers)
Date: 2021
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