Random Demand There Is A One-way Alternative Service Capacity Decision Model Study

Along with the rapid development of economy, service industry increasingly turns out to be a key role in our society. Studies on service and service industry have become more and more important in these years. The problems of matching service capacity supplies with demands, the tradeoffs between cost and income, are active areas of study. This paper studies the service capacity decision problem faced by service providers, i.e., how to set the right amount of service capacities to meet time-dependent stochastic demands, in order to make the maximum profit.In this paper we consider a service-provider who has to decide the right amount of substitutable service capacities under time-dependent stochastic demands to make the maximum profit. The amounts of capacities would be unchangeable once they have been set, while service capacities are perishable and can't be stocked. To solve this problem, we develop a general profit maximization model for service capacities decision problem, under time-dependent stochastic demand, with downward substitution, and show that it is concave and submodular. Then we obtain the optimal condition for service capacity amounts. We also show the effect of using substitution tactic on the increase of total profit.Then by computational study, we demonstrate the gains from computing the optimal solution. We study the impact of parameters, such as the per unit income of performing a service, the per unit income of substitution and the per unit cost of service capacities, and get some interesting conclusions, which may be helpful for service providers to make a better decision.