Optimal Control of Brownian Inventory Models with Convex Holding Cost: Average Cost Case

TL;DR

This paper analyzes optimal control policies for Brownian inventory models with convex holding costs, establishing the optimality of control band policies for both impulse and singular control cases using a verification theorem approach.

Contribution

It proves the existence of smooth solutions to the free boundary problem and demonstrates the optimality of control band policies in Brownian inventory models with convex costs.

Findings

Optimal control band policies are proven to be optimal.

Existence of smooth solutions to the free boundary problem is established.

Numerical algorithms for computing control parameters are developed.

Abstract

We consider an inventory system in which inventory level fluctuates as a Brownian motion in the absence of control. The inventory continuously accumulates cost at a rate that is a general convex function of the inventory level, which can be negative when there is a backlog. At any time, the inventory level can be adjusted by a positive or negative amount, which incurs a fixed cost and a proportional cost. The challenge is to find an adjustment policy that balances the holding cost and adjustment cost to minimize the long-run average cost. When both upward and downward fixed costs are positive, our model is an impulse control problem. When both fixed costs are zero, our model is a singular or instantaneous control problem. For the impulse control problem, we prove that a four-parameter control band policy is optimal among all feasible policies. For the singular control problem, we prove that a two-parameter control band policy is optimal. We use a lower-bound approach, widely known as "the verification theorem", to prove the optimality of a control band policy for both the impulse and singular control problems. Our major contribution is to prove the existence of a "smooth" solution to the free boundary problem under some mild assumptions on the holding cost function. The existence proof leads naturally to numerical algorithms to compute the optimal control band parameters. We demonstrate that the lower-bound approach also works for Brownian inventory model in which no inventory backlog is allowed. In a companion paper, we will show how the lower-bound approach can be adapted to study a Brownian inventory model under a discounted cost criterion.