A simulation-based algorithm for supply chain optimization

In a supply chain, there are wide variety of problems, such as transportation scheduling problems and warehouse location problems. These problems are independently defined as optimization problems, and algorithms have been proposed for each problem. It is difficult, however, to design an algorithm for optimizing a supply chain simultaneously because the problem is much more complex than the individual problems. We present a simulation-based optimization algorithm that optimizes a supply chain, exploiting both simulation and optimization techniques. This system leverages two existing algorithms, and will optimize a supply chain by executing simulations while changing the boundary conditions between the two algorithms. Experimental results show that a better solution to a supply chain can be found through a series of optimization simulations. A logistics consultant was satisfied with the solution. This system will be used in actual logistics consulting services.