Algorithm-based optimization of spare parts inventory management

Authors

  • Houda ELHADAF Department of Industrial Engineering, EIGSI Casabalanca, Morocco
  • Abdelilah JRAIFI University Cadi Ayyad, ENSA-S, MISCOM-Laboratory, Morocco

DOI:

https://doi.org/10.19139/soic-2310-5070-2552

Keywords:

Spare part, Genetic algorithm, Inventory, Optimization, Markov decision model

Abstract

This research aims to identify the most effective strategy for determining the ideal quantity of spare parts to order during each period, with the ultimate goal of minimizing management costs. These costs encompass various expenses associated with inventory management. To achieve this objective, we present a mathematical model of single-echelon inventory dynamics using a Markov decision model. Additionally, a method based on genetic algorithms is introduces to simultaneously minimize costs and maximize service levels. Therefore, the overarching objective of this article is to establish optimal inventory levels for a variable periodic demand inventory model. In order to illustrate the the effectiveness of the proposed method, a numerical example is given.

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Published

2025-10-06

How to Cite

ELHADAF, H. ., & JRAIFI, A. (2025). Algorithm-based optimization of spare parts inventory management. Statistics, Optimization & Information Computing, 15(2), 1036–1049. https://doi.org/10.19139/soic-2310-5070-2552

Issue

Vol. 15 No. 2 (2026): I2CEAI24

Section

Research Articles

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