document: Exploiting structure in adaptive dynamic programming algorithms for a stochastic batch service problem The purpose of this paper is to illustrate the importance of using structural results in dynamic programming algorithms . We consider the problem of approximating optimal strategies for the batch service of customers at a service station . Customers stochastically arrive at the station and wait to be served , incurring a waiting cost and a service cost . Service of customers is performed in groups of a fixed service capacity . We investigate the structure of cost functions and establish some theoretical results including monotonicity of the value functions . Then , we use our adaptive dynamic programming monotone algorithm that uses structure to preserve monotonicity of the estimates at each iterations to approximate the value functions . Since the problem with homogeneous customers can be solved optimally , we have a means of comparison to evaluate our heuristic . Finally , we compare our algorithm to classical forward dynamic programming methods
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