Yongbo Xiao

Product selection, machine time allocation, and scheduling decisions for manufacturing perishable products subject to a deadline

We are concerned about the following problem: a manufacturer owns a certain amount of perishable raw material which can be produced into different types of products. He must, however, finish the manufacturing process before a deadline (which represents, e.g., a fixed flight schedule). Due to the deadline constraint and the raw material limit, it is imperative for the manufacturer to determine three decisions: (i) the product types to be produced; (ii) the machine time to be allocated for each product type; and (iii) the sequence to process the products selected. We develop, in this paper, a model to formulate this problem. We show that (i) and (iii) can be determined by analytical rules, and (ii) can be computed by an efficient algorithm. The optimal policy with the three decisions for the problem is therefore completely constructed. We also show the relationships of our model to stochastic scheduling and stochastic knapsack, and discuss the contributions of our work to the two areas.

Optimal inventory and admission policies for drop-shipping retailers serving in-store and online customers

This article studies the optimal inventory and dynamic admission policies of two physical retailers who, besides selling through their traditional in-store channels, also act as drop-shippers for an online retailer (e-tailer). The e-tailer carries no inventory of its own and always turns to one of the two physical retailers for order fulfillment. The considered scenario is the one in which retailer 1 (R1) and retailer 2 (R2) act as the primary and secondary drop-shippers of the e-tailer, respectively. While trying to maximize their respective revenues, both retailers face the problem of whether or not to accept the e-tailers order-fulfillment request. It is initially assumed that the initial inventory levels of each retailer are fixed and that R1 shares his inventory information with R2. By adopting a revenue management framework, the dynamic admission policies of both retailers are studied and it is shown that R1 and R2 should implement one-dimensional and two-dimensional threshold policies, respectively. The scenario in which R1 does not share his inventory information with R2 is considered. For this scenario two heuristic policies for R2 are proposed and they are compared to the optimal policy when information is shared. A detailed sensitivity analysis for varying parameter value is presented, which shows the impact of information sharing between the two retailers. Finally, the assumption of fixed initial inventory levels is relaxed and the optimal initial inventory levels of each retailer that maximize their expected profits are determined.

Supply Chain Management of Fresh Products with Producer Transportation

This article considers a class of fresh-product supply chains in which products need to be transported by the upstream producer from a production base to a distant retail market. Due to high perishablility a portion of the products being shipped may decay during transportation, and therefore, become unsaleable. We consider a supply chain consisting of a single producer and a single distributor, and investigate two commonly adopted business models: (i) In the “pull” model, the distributor places an order, then the producer determines the shipping quantity, taking into account potential product decay during transportation, and transports the products to the destination market of the distributor; (ii) In the “push” model, the producer ships a batch of products to a distant wholesale market, and then the distributor purchases and resells to end customers. By considering a price-sensitive end-customer demand, we investigate the optimal decisions for supply chain members, including order quantity, shipping quantity, and retail price. Our research shows that both the producer and distributor (and thus the supply chain) will perform better if the pull model is adopted. To improve the supply chain performance, we propose a fixed inventory-plus factor (FIPF) strategy, in which the producer announces a pre-determined inventory-plus factor and the distributor compensates the producer for any surplus inventory that would otherwise be wasted. We show that this strategy is a Pareto improvement over the pull and push models for both parties. Finally, numerical experiments are conducted, which reveal some interesting managerial insights on the comparison between different business models.

Dynamic Inventory Transshipment Game between Two Retailers of Seasonal Products

Abstract Motivated by the common practice that competitive retailers usually transship inventories between each other to increase sales, this article studies the optimal transshipment policies of two retailers selling a same kind of seasonal or fashionable products in a same market. In the problem under investigation, before the selling period begins, both retailers hold a certain quantity of initial inventories that are non-replenishable during the selling process. Once one of the retailers has run out of its inventory, it can rely on the inventory that is transshipped from the other retailer to fulfill its customer. However, as a self-revenue maximizer, the other retailer can reject any transshipment requests. On basis of a discrete-time dynamic programming model, we study the optimal transshipment policies of the two retailers, and characterize the structural properties of their revenue functions. Moreover, we conduct a comparison of the decentralized system with the centralized system where both retailers seek to maximize their joint revenue. Numerical experiments show that though transshipment can increase revenue for both retailers, however, the competition between the retailers can induce a great total revenue loss.

On a semi-dynamic pricing and seat inventory allocation problem

Motivated by the practice of airlines, this paper considers the following problem. Tickets are offered at a limited number of predetermined price levels, and the price is only allowed to change monotonically. Management needs to determine the number of seats to be sold at each discount fare with an objective of maximizing the revenue. Such a semi-dynamic pricing and seat allocation approach improves the static pricing approach, as it allows a certain degree of pricing flexibility, but it compromises the potential revenue maximization of the dynamic pricing approach. Therefore, a natural question is what is the magnitude of the revenue loss by such a semi-dynamic approach? The primary objective of this paper is to gain insights into this question. Based on structural results, numerical experiments show that the semi-dynamic pricing approach generates near-optimal revenue.

Optimal Decisions of the Manufacturer and Distributor in a Fresh Product Supply Chain Involving Long-Distance Transportation

We consider a supply chain in which a distributor procures from a manufacturer a type of fresh product, which has to undergo long distance transportation before reaching the market. In addition to the risk caused by random fluctuations of the market demand, the distributor also faces the risk that the product procured may decay and deteriorate during transportation. The market demand for the product depends on its level of freshness and the distributor’s selling price. The manufacturer has to determine his wholesale price based on its effect on the order quantity of the distributor, whereas the distributor has to determine his order quantity and selling price, based on the wholesale price, the likely loss of the product in long distance transportation, the product’s level of freshness when it reaches the market, and the possible demand for the product. We develop a model to formulate this problem, and derive each party’s optimal decisions in both uncoordinated and coordinated situations. We introduce a new incentive scheme to facilitate the coordination of the two parties, which comprises two parts: (1) the manufacturer offers his wholesale price as a function of the actual transportation time and price discount in the market; and (2) the manufacturer compensates the distributor for any unsold unit of the product. We show that this incentive scheme can induce the distributor to order up to the quantity required to maximize the total benefit of the centralized system, and both parties will all be better off than in the uncoordinated case. Computational studies are also conducted, which reveal some interesting managerial insights.