Simulation-Based Evolutionary Optimization of Complex Multi-Location Inventory Models

A common strategy to solve real-world problems in economics that cannot be solved analytically is the simulation-based optimization approach, which requires the complete simulation of the system to evaluate its configuration. This idea is illustrated for a very general class of logistics systems, represented by multi-location inventory models with lateral transshipments, applying evolutionary optimization. These systems have become increasingly important in a globalized economic setting and strategies for the control of transshipments are questions of current research. In particular, we extend existing approaches by considering the future behavior of the system in order to reallocate or to increase assets.