A budgeting resource allocation model for capacity expansion

Abstract

The reconfiguration of the global supply chain has created opportunities for newly industrialized economies (NIEs) to strengthen and expand their production capacities. We develop a dynamic modeling framework to study a firm’s resource allocation decisions while building capacity for a portfolio of production lines over multiple decision periods. Our model adds to the literature on versions of this problem in which distributions of market demands are incorporated into the investment–return function, and where no partial order fulfillment is possible. We consider two specific cases: one involving exogenously defined demand distributions, and one where the distributions of the parameters of the demand distribution are updated based on Bayesian inference. For each case, we first identify optimal capacity levels as a function of unit investment cost, holding cost, and the demand distribution of each production line. We then characterize the optimal path to reach these levels under different market conditions by deriving closed-form optimal resource allocation policies.