APPLYING ANT COLONY ALGORITHM FOR TRANSPORT OPTIMIZATION IN TEXTILE INDUSTRY SUPPLY CHAIN

Abstract

One of the major issues in the textile industry’s supply chain logistics is transportation, specifically cost, efficiency, and delivery timeframe. This study investigates using the Ant Colony Optimization (ACO) algorithm as a promising method of transport optimization in textile industry logistics. The ACO model uses the same mechanisms as the ants; it considers using more than one distribution point, including many important factors such as distance and fuel. We will elaborate on the entire framework of ACO, with particular emphasis on updating the rules of pheromones and virtual ants’ decision-making process. This study illustrates the application of the ACO model in textile logistics, employing case studies and computer modeling, leading to more significant cost savings and improved service levels in the industry. In practice, the ACO theory improves the supply chain’s transportation efficiency, flexibility, and environmental sustainability, giving the textile industry a competitive edge in emerging markets.