Reactive Hybrid Particle Swarm Optimization Based Job-shop Scheduling Problems Considering Energy Management

Abstract

This paper presents reactive hybrid particle swarm optimization based job-shop scheduling problems considering energy management. Since reduction of energy costs is important, operational planning of energy plants in factories should be optimized. However, the scheduling in factories and optimization of energy plants have been solved separately. Namely, energy costs have been ignored when the scheduling is optimized. However, it should be considered from the management point of view. This paper tries to optimize production scheduling and energy plant in order to minimize the maximum end time of all factory operations (makespan) and total energy costs simultaneously. Effectiveness of the proposed method is verified through simulations with 10 jobs 10 machines problem and it is verified that the proposed method can obtain higher quality solutions than the conventional method.