Innovative Resource Distribution Through Multi-Agent Supply Chain Scheduling Leveraging Honey Bee Optimization Techniques

Many people and things involved in the supply chain can be represented by a network of linked agents in a multi-agent system. To achieve distribution and manufacturing targets efficiently, actions in a supply chain must be scheduled by tracking and organizing the allocation of resources. Healthcare, energy, aerospace, agriculture, and manufacturing are some of the industries that make use of it to better allocate and coordinate resources in complex networks. The goal of multi-agent supply chains is to lower costs and meet demand in dynamic contexts through efficient resource allocation and planning. Traditional approaches, such as linear programming and heuristic algorithmic approaches, have problems with adaptation and scalability. This study offers a novel scheduling method, Resource Distribution by Honey Bee Optimization (RDHBO), to circumvent these issues. It is based on a tactic that the honey bee uses when foraging. In this model, scout bees and foragers take on the role of actors, investigating and making the most of potential new ways to divide up resources by employing HBO strategies. The foraging agents look for places that have been profitable in the past, and the scouting agents carefully examine the supply chain to find places where resources might be available. The proposed RDHBO architecture allows for better supply chain scheduling by encouraging effective utilization and investigation, better communication, dynamic adaptability, autonomous decision-making, and efficiency of complicated systems. This method leads to an adaptable supply chain, lower operational costs, and more scalability and adaptability. This paper presents a formidable alternative to conventional optimization methods by demonstrating an efficient approach to dealing with complicated supply chain challenges.

Keywords :

Multi-agent system, Honeybee optimization, Resource distribution, Supply chain, Resource allocation, Scalability, and Adaptability