Article ID Journal Published Year Pages File Type
477969 European Journal of Operational Research 2015 12 Pages PDF
Abstract

•A firm aims at meeting a random demand at the end of a random time interval.•The firm increases inventory buying on a spot market and maximizes expected profits.•We take exponential Lévy spot prices and a general convex holding cost function.•First order conditions completely characterize the optimal procurement policy.•An analytic explicit solution is provided for linear holding costs.

In this paper we study a continuous time stochastic inventory model for a commodity traded in the spot market and whose supply purchase is affected by price and demand uncertainty. A firm aims at meeting a random demand of the commodity at a random time by maximizing total expected profits. We model the firm’s optimal procurement problem as a singular stochastic control problem in which controls are nondecreasing processes and represent the cumulative investment made by the firm in the spot market (a so-called stochastic ‘monotone follower problem’). We assume a general exponential Lévy process for the commodity’s spot price, rather than the commonly used geometric Brownian motion, and general convex holding costs.We obtain necessary and sufficient first order conditions for optimality and we provide the optimal procurement policy in terms of a base inventory process; that is, a minimal time-dependent desirable inventory level that the firm’s manager must reach at any time. In particular, in the case of linear holding costs and exponentially distributed demand, we are also able to obtain the explicit analytic form of the optimal policy and a probabilistic representation of the optimal revenue. The paper is completed by some computer drawings of the optimal inventory when spot prices are given by a geometric Brownian motion and by an exponential jump-diffusion process. In the first case we also make a numerical comparison between the value function and the revenue associated to the classical static “newsvendor” strategy.

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Physical Sciences and Engineering Computer Science Computer Science (General)
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