Simulation modeling in heterogeneous distributed computing environments to support decisions making in warehouse logistics

We address an important problem of automation in simulation modeling of logistics warehouses. An effective solution for such a large-scale problem is difficult to obtain without high-performance computing. To this end, we propose a new approach for adjusting management system parameters of the warehouse in its production use. It is based on the integration of conceptual, wireframe, and service-oriented programming used to develop parameter sweep applications and data analysis in simulation modeling in heterogeneous distributed computing environments. We design a toolkit to support modeling of warehouse logistics. Using this toolkit, we develop a parameter sweep application and solve three optimization tasks for adjusting parameters of a warehouse management system. The practical experiments are focused on the refrigerated warehouse. The developed applications demonstrate high efficiency and scalability capabilities to optimize nine criteria to cope with different production demands.