Simulation and experimental design methods for job shop scheduling with material handling: a survey

Job shop scheduling (JSS) problems have been studied for over six decades. Many of them are proved to be non-deterministic polynomial-time (NP) hard, which means that they are intractable and the computation time increases exponentially with the problem size goes up. Some assumptions have been made in the previous studies about JSS problems in order to simplify the model and solve it. One of those assumption is that the transferring times of jobs between different machines are negligible. However, it is highly not practical not to model the material handling activities in a typical shop floor scheduling problems in reality, especially when the movements of jobs on shop floor are completely relying on the material handling equipment and the transferring times are comparable to the production times. Omitting the transferring times will make the result of scheduling impossible to be implemented. Therefore, many recent studies have been done about Job shop scheduling with material handling (JSPMH/JSSMH). The problem has been defined into two different categories: offline and online scheduling problems. Offline scheduling means solving JSSMH problem as static scheduling problem that is solved before shop floor starts its production with known or predicted information of orders, while online scheduling is dynamic scheduling problem that is solved to generate schedules in real time as orders arrive on the shop floor. In both methods, the simulation modeling tool has been widely used with its ability of efficiently searching for optimal solution as well as evaluating the results. In articles that study the JSSMH problems as the dynamic scheduling, simulation method has been popularly used to factor in various scenarios of production. Our review will comprehensively summarize how JSSMH problems are solved in dynamic and static problem settings, as well as how simulation models play a useful role in solving this type of problems.