Open Access
Journal Article
Swarm Intelligence Algorithms for Supply Chain Optimization
by
Sophia Anderson
TASC 2023 5(2):43; 10.69610/j.tasc.20231022 - 22 October 2023
Abstract
Swarm intelligence algorithms have emerged as a promising approach for solving complex optimization problems in various domains, and supply chain management is no exception. This paper discusses the application of swarm intelligence algorithms for optimizing supply chain operations. We begin by providing a brief overview of the principles of swarm intelligence and how they can
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Swarm intelligence algorithms have emerged as a promising approach for solving complex optimization problems in various domains, and supply chain management is no exception. This paper discusses the application of swarm intelligence algorithms for optimizing supply chain operations. We begin by providing a brief overview of the principles of swarm intelligence and how they can be harnessed to address the complexities of supply chain management. We then delve into the different types of swarm intelligence algorithms, including ant colony optimization, particle swarm optimization, and bee swarm intelligence, highlighting their unique characteristics and advantages. The paper further explores case studies and real-world applications where these algorithms have been successfully implemented to enhance supply chain efficiency, reduce costs, and improve decision-making processes. We conclude by identifying the future research directions for integrating swarm intelligence algorithms with advanced technologies such as artificial intelligence, big data, and the Internet of Things.