Real options and networks.

Over the past few years' researchers have investigated fixing the problems of allocating resources effectively maintaining cost efficiency in telecommunications and electricity networks. The ideal network configuration would maximize coverage, capacity, quality-of-service and deploy optimal investment models to negotiate the uncertainties of demand and shortcomings in network architecture. In this dissertation we introduce new ways to analyze optimization of telecommunications and electricity networks. The first part of the dissertation considers call routing in a telecommunications network. The network demands are assumed to be driven by Brownian motions and call routing takes place either directly or alternatively via an intermediate node. The expected routing processes and blocking probabilities are solved in terms of trivariate normal distributions. We consider the effects of demand uncertainty levels and their correlations on call routing and illustrate our model with a numerical example. Further, we show how our model can be used with a usual call routing method. In the second part of the dissertation, we formulate a game model for electricity market participants. Our model allows the government to regulate the participants to avoid blackouts and to maximize its revenues at the same time. We solve the equilibrium numerically using Stackelberg leadership model. Our results give insights of the factors that drive the system equilibrium. Further, it suggests how the government should regulate the market participants.Ph.D.Applied SciencesIndustrial engineeringOperations researchUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/126426/2/3253275.pd