A methodology to improve simulation optimization approach for process scheduling through Petri net formalism

摘要

Simulation models have proved to be useful for examining the performance of alternative system configurations and/or alternative operating procedures for complex systems. It is widely acknowledged that simulation is a powerful computer-based tool that enables decision-makers in business and industry to improve operational and organizational efficiency. However, when applying simulation techniques to improve logistic systems performance, several limitations arises due to its inability to evaluate more than a fraction of the immense range of options available. Present commercial simulation software packages have integrated optimization tools trying to give a proper answer as decision support tools to present industrial demands where the decision task usually involve technological or economical risk. Simulation optimization is one of the most popular approaches to improve the use of simulation models as a tool to obtain in a short time the best (optimal or quasi-optimal) decision variables values that minimize a certain objective function. However, despite the success of several simulation-optimization packages, many technical hurdles and barriers to afford the performance improvement of system in different application domains still remain. In this paper we will describe a new approach to integrate evaluation methods with search methods based on not only simulation results, but using also information from the simulation model.