An Approximation of a Markov Decision Process for Resource Planning

Abstract

This study presents an approximation of a Markovian decision process to calculate resource planning policies for environments with probabilistic resource demand. These policies provide a means of periodic determination of the quantity of resources required to be available. Managers may also use these approximation models to perform the sensitivity analysis of resource demand and the cost/reward parameters. The decision policy can be applied to many resource planning situations including manufacturing or construction equipment purchasing or leasing, airline capacity, professional services staffing, and computer/management information systems capacity.

Keywords:

• stochastic processes
• resource planning
• mathematical programming
• regression analysis
• heuristics