Modeling and simulation optimization systems design for job shop problems based on Arena

Considering the inherent complexity of job shop problems, especially its difficulty in analytical solving, an integrated system framework is established. First, a general-purpose and powerful simulator, Arena, is employed for modeling job shop problems, and a kind of virtual preemption rule is recommended to enhance the modeling capability. Then an efficient optimization procedure GRASP is designed for finding the optimal solution. By taking advantage of Arena class library, the interaction between Arena and GRASP has been effectively implemented, and an integrated framework is thus achieved. With this framework, various stochastic factors can be conveniently introduced into the model; hence the capability for modeling the real-life systems is greatly improved. Finally, an example is analyzed to demonstrate the effectiveness of the method.