Stochastic task selection and renewable resource allocation

Abstract
A class of renewable-resource-allocation problems is studied for the processing of dynamically arriving tasks with deterministic deadlines. The model presented explicitly considers time available, time required, resources available, resources required, stochastic arrivals of multiple types of tasks, importance of tasks, timeliness of processing, and accuracy of resource allocation. After state augmentation, the problem becomes a Markovian decision problem, and can be solved, at least in principle, by using a stochastic dynamic programming (SDP) method. Effects of key system parameters on optimal decisions are investigated and analyzed through numerical examples.

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