Solution of the Spare Parts Joint Replenishment Problem with Quantity Discounts Using a Discrete Particle Swarm Optimization Technique

Orlando DURÁN¹, Luis PÉREZ²
¹Pontificia Universidad Católica de Valparaiso
Valparaiso, Chile
orlando.duran@ucv.cl
²Universidad Técnica Federico Santa Maria
Valparaiso, Chile
luis.perez@usm.cl

Abstract: Joint Replenishment of spare parts is a common practice in several industries, mainly where logistic difficulties exist, such as mining, petroleum and military missions. In addition, quantity discounts have been considered in many operations and production scenarios, as a useful practice to promote substantial savings to the actors of a supply chain. The model presented corresponds to the Joint Replenishment Problem in a system operating with quantity discounts. This work presents the definition and the solution of the optimization model using techniques based on the Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA). Extensive computational experiments were performed and several performance comparisons are included. Results clearly show that the PSO algorithm achieved better repeatability and the GA presented better performance in terms of minimization capability getting lower fitness values.

Keywords: joint replenishment problem, quantity discounts, metaheuristics, particle swarm, genetic algorithm, logistics.

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CITE THIS PAPER AS:
Orlando DURÁN, Luis PÉREZ, Solution of the Spare Parts Joint Replenishment Problem with Quantity Discounts Using a Discrete Particle Swarm Optimization Technique, , Studies in Informatics and Control, ISSN 1220-1766, vol. 22 (4), pp. 319-328, 2013. https://doi.org/10.24846/v22i4y201307