Enhancing Scalability and Resource Management for Large-Scale Multi-Agent System Deployments

The Intelligent Adaptive Predictive Energy Management (IAPEM) framework demonstrates superior performance as a novel multi-agent system to solve scalability and dynamic variability and human-AI integration challenges in large-scale industrial energy optimization. The structured architecture of IAPEM combined with its hybrid algorithmic strategy and human-in-the-loop mechanisms enables substantial energy and cost efficiencies to overcome fundamental limitations of predictive or less integrated approaches despite the complexities of real-world integration with diverse legacy systems and unforeseen environmental factors. The simulated multi-machine conveyor system validation of IAPEM resulted in a 25% energy reduction and 18% cost decrease together with 30% faster responsiveness and 40% less idle time (p<0.05). The proven linear scalability and robust performance of this system demonstrate its potential as a sustainable and