Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Evolutionary Optimization in Supply Chain Management

Oliver Chen
Senior Researcher, Health Technology Institute, Maplewood University, Vancouver, Canada
Cover

Published 16-04-2023

Keywords

  • Evolutionary Optimization,
  • Supply Chain Management,
  • Logistics,
  • Inventory Management

How to Cite

[1]
Oliver Chen, “Evolutionary Optimization in Supply Chain Management”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 43–53, Apr. 2023, Accessed: Dec. 24, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/5

Abstract

Supply chain management (SCM) plays a critical role in the success of businesses by ensuring the efficient flow of goods and services from suppliers to customers. With the increasing complexity and global nature of supply chains, traditional optimization methods are often insufficient to handle the dynamic and interconnected nature of supply chain operations. Evolutionary optimization techniques, inspired by natural evolution, offer a promising approach to address these challenges. This paper provides a comprehensive review of the application of evolutionary optimization methods in SCM, focusing on their use in optimizing logistics, inventory management, and distribution networks. We discuss the principles of evolutionary optimization and its application in SCM, including genetic algorithms, evolutionary strategies, and other related techniques. Furthermore, we examine the benefits and challenges of using evolutionary optimization in SCM and provide insights into future research directions in this field.

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