The Study Of Multi-Objective Optimization Of Supply Chain Pillars Using Bat Algorithm

The supply chain pillars are the key factors that help the organization to achieve high efficiency which were and are an area of investigation for continuous improvement. The BAT Algorithm inspired by the echolocation behaviour of BATs, has emerged as a powerful metaheuristic optimization tool used across various domains including supply chain management. This article explores the application and effectiveness of the BAT Algorithm in optimizing supply chain networks, addressing complex problems of supply chain pillars such as inventory control, demand forecasting, distribution routing, and dispatch. The BAT Algorithm's ability to balance global exploration and local exploitation allows for efficient and effective solutions in dynamic and uncertain supply chain environments. This article focuses on the workings of the BAT Algorithm considering factors like frequency, loudness, and pulse rate. This paper investigates the different aspects and identifies how this aid in multi-objective optimization and help create more sustainable working supply chain networks. This research is based on secondary data covering literature articles, and case studies, where the BAT Algorithm has been successfully implemented, demonstrating significant cost reduction, improved resource allocation, and overall performance.