A decision support system based on simulation optimization

Abstract

Modeling and simulation is a powerful industrial engineering technique for gaining insights into the functioning, performance, and operation of complex systems. It is an extremely useful tool for stake holders and decision makers in different industries. By changing the operating parameters and input data to a system under investigation with simulation, assessment and forecasts about the behaviors of the systems can be obtained through computer-aided simulation, hence revealing the salient information to assist management to make the right decisions. While it is well acknowledged that the deployment of simulation produces feasible solutions under certain conditions for system analysis, such solutions may not be optimal and is often inadequate in circumstances where optimality is required. With this regards, this paper presents a framework that combines the process of optimization and simulation such that the strengths of both techniques are combined. This proposed simulation-based optimization framework integrates the meta-heuristics of an artificial intelligence method with a simulation engine supported by an industrial grade simulation tool for the evaluation of optimal system parameters and to reveal the performance of a system.