Reactive Tabu Search for Job-shop scheduling problems considering peak shift of electric power energy consumption

The Job-shop scheduling problem (JSP) can be formulated as a combinatorial optimization problem. Up to now, the problem has been solved by various evolutionary computation techniques such as Genetic Algorithm (GA) and Tabu Search (TS). Recently, practical methods for the JSP considering various practical constraints have been developed. However, methods for the JSP considering peak shift of electric power energy consumption have not been developed yet. This paper presents an application of Reactive Tabu Search for the JSP considering the peak shift of electric power energy consumption.