Ant colony intelligence in agent coordination for dynamic manufacturing scheduling

This study aims at building an efficient agent-based dynamic scheduling for real-world manufacturing systems with various products, processes, and disturbances. Ant colony intelligence is proposed to be combined with local agent coordination so as to make autonomous agents adaptive to changing circumstances and to give rise to efficient global performance. Ant colony intelligence integrated with both machine agents and job agents to solve not only the task allocation problem, but also the task sequencing problem. Simulation results show that, for most of the performance measures, a MAS integrated with well-designed ant inspired coordination performs well compared to a MAS using dispatching rules.