Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods

Abstract

A dynamic capacity allocation problem is considered in this paper. A fixed amount of daily processing capacity is allowed. Jobs of different priorities arrive randomly over time and a decision is required on which jobs should be scheduled on which days. The jobs that are waiting to be processed incur a holding cost depending on their priority levels. The objective is to minimize the total expected cost over a planning horizon. In this paper the focus is on a class of policies that are characterized by a set of protection levels. The role of the protection levels is to “protect” a portion of the capacity from the lower priority jobs so as to make it available for the future higher priority jobs. A stochastic approximation method to find a good set of protection levels is developed and its convergence is proved. Computational experiments indicate that protection level policies perform especially well when the coefficient of variation for the job arrivals is high. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Technical appendix detailing the proofs of propositions.]