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| Modeling Cybercafé Internet Service for Revenue Optimization under Stochastic Demand |
Kizito P Mubiru, Senfuka Christopher, Ssempijja Maureen
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Abstract:
We consider a set of cybercafés faced with an optimal choice of bandwidth for internet service under stochastic stationary demand. The choice is made over uniformly time horizons with a goal of optimizing revenue for internet service provision. Considering customer demand and price for internet service at cybercafés, we formulate a finite state markov decision process model where states of a markov chain represent possible states of demand for internet service. A revenue matrix is generated; representing the long run measure of performance for the Markov decision process problem. The problem is to determine an optimal bandwidth adjustment policy at cybercafés so that the long run revenue generated is maximized for a given state of demand. Using dynamic programming, the optimal bandwidth adjustment policies are determined over a finite period planning horizon. Results from the case study demonstrate the existence of an optimal state-dependent option for bandwidth adjustment policy and revenue generated from internet service provision at the cybercafés.
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