Improved Parallel Reactive Tabu Search Based Job-Shop Scheduling Considering Minimization of Secondary Energy Costs in Factories

This paper proposes improved parallel RTS and presents its application to job-shop scheduling considering minimization of the secondary energy costs in factories. The method considers not only optimal production scheduling but also optimal operation of energy plants simultaneously in order to minimize the secondary energy costs. Recently, actual production schedules are changing from single and mass production to various kinds of small quantity production. In order to deal with the change, for obtaining high quality solutions, and for obtaining solutions quickly, improved parallel RTS using parallel computation is proposed. The proposed method is applied to 10 jobs 10 machines and the results indicate that it has a possibility to minimize not only makespan of the scheduling but also the secondary energy costs of energy plants. Using the improved parallel reactive tabu search using parallel computation, the proposed method can reduce processing time as well.