Dynamic pricing and replenishment in the warehouse scheduling problem—A common cycle approach

Abstract

In this paper, we consider the problem at the interface of marketing and operations to find the optimal lot-size and selling price for multiple products that share a warehouse with limited storage capacity. We analyze the impact of coordinated decision making on the selling price and the replenishment policy compared to a decentralized decision. Furthermore, we compare constant pricing where the selling price remains constant over the entire planning horizon and dynamic pricing where the firm is allowed to adjust the selling price continuously. The objective is to maximize the average profit by choosing the optimal pricing strategy, the optimal lot-sizes, and the optimal staggering of the order releases. This paper provides both analytical and numerical results on the impact of a joint optimization on the pricing and replenishment decisions and the potential benefits compared to the decentralized approach. We develop mathematical models for the different decision frameworks, provide algorithms to determine the optimal policy parameters, and show that the peak storage requirement is equal at each replenishment. Furthermore, we show in a numerical example that achieving operational efficiency through dynamic pricing in the warehouse scheduling problem is even more beneficial than in the economic order quantity framework.