Computational Operations Research Issues

This chapter introduces Discrete and Continuous-Time Markov Chain Process aimed to predict the behavior of a waiting line, based on the probabilities of going from the state i to the state j, and also from velocity rates lambda and retracement mu. In both cases a numerical example is provided that shows the mechanics of both random walks as well as the pertinent observations when altering these parameters, and discusses the possibility of these parameters being altered in real time in an unsupervised algorithm. nbsp;