Offline Simulation Online Application: A New Framework of Simulation-Based Decision Making

Abstract

Traditionally, simulation has been used as a tool of design to estimate, compare and optimize the performance of different system designs. It is rarely used in making real-time decisions due to the long computation delay of executing simulation models. However, with the fast growth of computing capability, we have observed more and more works on reusing simulation efforts for repeated experiments with the help of data analytics tools, and the target of these works is to solve real-time decision problems. In this paper, we distill the important features of these works and summarize a new simulation framework, called offline-simulation-online-application (OSOA) framework, which treats simulation as a data generator, applies state-of-the-art analytics tools to build predictive models, and then uses the predictive models for real-time applications. In this paper, we illustrate how to apply the OSOA framework on estimation, ranking and selection and simulation optimization, and provide a prospect of this new framework.

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