A Large Neighborhood Local Search Method Incorporating MIP Techniques for Large-Scale Optimization Problems with Many constraints: Application to the Machining Scheduling

This paper addresses the problem of scheduling machining operations in a highly automated manufacturing environment, while considering the work styles of workers. In actual manufacturing, many issues must be considered, for example, constraints related to the works to be machined in the machining schedule and workers' states. To derive good solutions for such a large-scale problem with many constraints in a realistic amount of computing time, we develop an optimization technique based on an MIP-based large neighborhood local search method for the machining scheduling problem. Then, computer experiments are performed for a problem based on actual machining requirements to verify the validity of the proposed method.