Dynamic Order Acceptance and Capacity Planning within a Multi-Project Environment

Abstract

We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for regular as well as nonregular capacity. We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as an optimal capacity allocation for accepted projects, both with an eye on maximizing the expected revenues within the problem horizon. We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selectionand capacity usage.