Structure of Optimal Solutions to Periodic-Review Total-Cost Inventory Control Models with Convex Costs and Backorders for all Values of Discount Factors

TL;DR

This paper characterizes the structure of optimal inventory policies in discounted periodic-review models with convex costs and backorders, including cases where traditional assumptions do not hold, for both finite and infinite horizons.

Contribution

It introduces a parameter that, along with discount factors and horizon length, determines the structure of optimal policies, extending existing results to more general cases.

Findings

Optimal policies can be of three types depending on parameters.

For infinite horizon, policies are either $(s,S)$ or never order.

Finite horizon policies vary with time, parameters, and horizon length.

Abstract

This paper describes the structure of optimal policies for discounted periodic-review single-commodity total-cost inventory control problems with fixed ordering costs for finite and infinite horizons. There are known conditions in the literature for optimality of $(s_t,S_t)$ policies for finite-horizon problems and the optimality of $(s,S)$ policies for infinite-horizon problems. The results of this paper cover the situation, when such assumption may not hold. This paper describes a parameter, which, together with the value of the discount factor and the horizon length, defines the structure of an optimal policy. For the infinite horizon, depending on the values of this parameter and the discount factor, an optimal policy either is an $(s,S)$ policy or never orders inventory. For a finite horizon, depending on the values of this parameter, the discount factor, and the horizon length, there are three possible structures of an optimal policy: (i) it is an $(s_t,S_t)$ policy, (ii) it is an $(s_t,S_t)$ policy at earlier stages and then does not order inventory, or (iii) it never orders inventory. The paper also establishes continuity of optimal value functions and describes alternative optimal actions at states $s_t$ and $s.$