SINGLE-RUN SIMULATION OPTIMIZATION THROUGH TIME DILATION AND OPTIMAL COMPUTING BUDGET ALLOCATION AND SOME APPLICATIONS

Abstract

Discrete event simulation has been widely applied to study the behavior of stochastic systems, for which no analytical solutions can be formulated. In fact, Simulation-Optimization techniques are employed to identify the system configuration which can maximize the expected system performance when this can only be estimated by running a simulator. This thesis looks into simulation-based optimization when a finite number of solutions are available and object is to identify the best. Time-dilation(TD) is the base technique employed in this thesis to combine single simulations to a concurrent one and it provides the approach to allocate computing resource respectively to different configurations. Combinations of TD with Optimal Computing Budget Allocation(OCBA) and other allocation rules are studied. Variance estimation in single run simulation environment is discussed. Performance of the method is studied through theoretical and real-life cases.