Optimisation of multi-plant capacitated lot-sizing problems in an integrated supply chain network using calibrated metaheuristic algorithms

Maryam Mohammadi, Siti Nurmaya Musa*, Mohd Bin Omar

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)

Abstract

In this paper, a mathematical model for a multi-item multi-period capacitated lot-sizing problem in an integrated supply chain network composed of multiple suppliers, plants and distribution centres is developed. The combinations of several functions such as purchasing, production, storage, backordering and transportation are considered. The objective is to simultaneously determine the optimal raw material order quantity, production and inventory levels, and the transportation amount, so that the demand can be satisfied with the lowest possible cost. Transfer decisions between plants are made when demand at a plant can be fulfilled by other production sites to cope with the under-capacity and stock-out problems of that plant. Since the proposed model is NP-hard, a genetic algorithm is used to solve the model. To validate the results, particle swarm optimisation and imperialist competitive algorithm are applied to solve the model as well. The results show that genetic algorithm offers better solution compared to other algorithms.

Original languageEnglish
Pages (from-to)325-363
Number of pages39
JournalInternational Journal of Operational Research
Volume39
Issue number3
DOIs
Publication statusPublished - 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • Capacitated lot-sizing
  • GA
  • Genetic algorithm
  • ICA.
  • imperialist competitive algorithm
  • Integrated supply chain
  • Metaheuristic algorithms
  • Multi-plant
  • Optimisation
  • Particle swarm optimization
  • Production and distribution planning
  • PSO

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