Analysis of Decision Stochastic Discrete-Event Systems Aggregating Max-Plus Algebra and Markov Chain

Many optimization problems are complex enough that their solutions must be measured through simulation. It is also known that simulation requires a huge computational effort which impacts directly on the optimization solution. Accordingly, this paper presents a hybrid methodology faster than standard simulation tools to deal with stochastic systems subject to synchronization, delay, and decision phenomena. Such methodology aggregates Max-Plus Algebra with Markov Chain for modeling a load haulage cycle of an open-pit mine. The goal is computing the expected value for total iron production. To show that this new methodology can be applied to compute the mentioned measure, an experiment analysis was conducted to compare the results obtained. The test has shown evidence of equivalence between the results acquired by the hybrid methodology and by a standard simulation tool.