Optimizing Energy-Conscious Dynamic Flexible Job Shop Scheduling: Multi-agent Simulation Approach

Nowadays, manufacturing industry around the world is facing strong economic pressures and enormous environmental challenges due to its huge energy consumption and associated environmental impacts. One of the effective strategies to reduce energy consumption is by employing intelligent scheduling techniques. In this paper, we propose a decision making tool, based on multi-agent simulation, to address the dynamic flexible job shop scheduling problem with transportation robots reducing energy consumption, transportation distance, waiting time and makespan simultaneously. Numerical experiments are carried out to evaluate the performance of the proposed model. The experimental results revealed that the proposed model can improve the energy saving without degrading the other objectives.