An Application of Hybrid Meta-heuristics to Consensus-based Distributed Scheduling

In recent years, the development of optimization methods in multi-agent systems has been remarkable. Most scheduling problems belong to NP-hard and it is not easy to solve them in large-scale systems. We have proposed applying the alternating direction method of multipliers for the consensus problem to the distributed scheduling problem and showed that the job shop scheduling problem is formulated by the consensus-based distributed scheduling problem. The distributed scheduling method is a method for finding a feasible solution by repeating solving subproblems and exchanging data. It is expected that it can be applied to large-scale problems. However, since subproblems also belong to NP-hard, there is a limit to the applicable scale. In this paper, we propose to use hybrid meta-heuristics to solve subproblems. For the scheduling problem of the rolling system, we constructed a hybrid meta-heuristic model using the local search method and mathematical programming method for the scheduling of the melt shop and evaluated the proposed method. The results of computer experiments show that meta-heuristics are effective for the consensus-based distributed scheduling method.