Simulation optimization of logistics systems through the use of variance reduction techniques and criterion models

Abstract

Simulation is a useful tool for modelling logistics systems. However, simulation itself is not an optimization tool. Therefore attempts have been made to combine simulation and optimization. Optimization of a logistics system through the use of simulation is difficult for several reasons. Because of the size and complexity of logistics systems, it is often necessary to consider the trade-offs between multiple conflicting performance measures for the system. One major drawback associated with commercially available tools is that users are not able to consider these trade-offs easily. To overcome this drawback, a simulation model can be developed to employ multi-objective decision analysis techniques such as criterion models which can then be optimized. This article illustrates how criterion models can be interfaced with simulation models of logistics systems. In addition, this article includes the programming and implementation of the variance reduction techniques of common random numbers and antithetic variates.