Joint Initial Stocking and Transshipment——Asymptotics and Bounds

该论文针对许多公司在供应链中面临的各分销中心周期性期初订货、期间可通过转运来再匹配各分销中心的供需不平衡问题，通过随机动态规划建模，刻画最优订货和转运策略，并证明最优订货和转运策略对总利润的贡献分别为T 和根号T 的量级，该结论的管理启示是期初订货决策的贡献比再分配重要得多，特别是对大批量、快消品行业。【Abstract】A common problem faced by many firms in their supply chains can be abstracted as follows. Periodically, or at the beginning of some selling season, the firm needs to distribute finished goods to a set of stocking locations, which, in turn, supply customer demands. Over the selling season, if and when there is a supply-demand mismatch somewhere, a re-distribution or transshipment will be needed. Hence, there are two decisions involved: the one-time stocking decision at the beginning of the season and the supply/transshipment decision throughout the season. Applying a stochastic dynamic programming formulation to a two-location model with compound Poisson demand processes, we identify the optimal supply/transshipment policy and show that the optimal initial stocking quantities can be obtained via maximizing a concave function whereas the contribution of transshipment is of order square-root-of T. Hence, in the context of high-volume, fast-moving products, the initial stocking quantity decision is a much more important contributor to the overall profit. The bounds also lead to a heuristic policy, which exhibits excellent performance in our numerical study; and we further prove both the bounds and the heuristic policy are asymptotically optimal when T approaches infinity. Extension to multiple locations is also discussed

Introduction to the special issue : management science in the fight against Covid-19

At the time of writing of this Editorial in April 2021, Covid-19 continues to ravage our planet, with an official global death toll now exceeding three million, and a horrendous legacy of economic and human damage. The roll-out of vaccination has given hope that we will soon reach the end of this chapter of history. However, it will take years for the world to overcome this calamity and many individuals whose health or livelihoods have been destroyed will never fully recover. This failure of the world to effectively respond to the challenge of Covid-19 is all the more bitter because the outbreak of a novel pathogen was entirely predictable; the spread, preventable; and the suffering, avoidable. The experience of different countries around the world shows that the ability to plan, and to execute plans in a disciplined fashion, can make all the difference between relative security and catastrophe. The challenge for Management Scientists is to show that our discipline can have a role – a critical role – as a part of this planning. Epidemiological models of disease dynamics have been prominent through this crisis but do not fully capture the constraints in the health system and cannot directly support many of the management decisions which have to be made as part of the response. As Management Scientists, our perspective and our modelling tools have the potential to address those shortcomings; but if our profession cannot demonstrate our ability to add value, others will do so in our place

Monotone optimal control for a class of discrete-event stochastic systems and its applications in revenue management

This dissertation studies monotone optimal control for a class of discrete-event stochastic systems and its applications in revenue management. It first provides a unified treatment for a class of discrete-event stochastic systems with applications in many different fields. Then it explores applications in three important revenue management problems: capacity control for multiple medical diagnostic facilities, dynamic pricing with two revenue streams, and risk-sensitive dynamic pricing.DOCTOR OF PHILOSOPHY (NBS

Monotone optimal control for a class of Markov decision processes

This paper provides a unified framework to study monotone optimal control for a class of Markov decision processes through D-multimodularity. We demonstrate that each system in this class can be classified as either a substitution-type or a complement-type system according to the possible transition set, which can be used as a classification mechanism that integrates a variety of models in the literature. We develop a generic proof of the structural properties of both types of system. In particular, we show that D-multimodularity is a generally sufficient condition for monotone optimal control of different types of system in this class. With this unified theory, there is no need to pursue each problem ad hoc and the structural properties of this class of MDPs follow with ease

Dynamic pricing with two revenue streams

We study casino revenue management through the pricing of hotel rooms in the presence of gaming revenue, which is random. We identify a stochastic order based on customers’ gaming profiles, from which a monotonic inventory price of rooms is obtained. We develop a threshold-type pricing policy for a special customer segmentation scheme that allows customers’ winning profiles to be ranked in terms of the failure rate order. Our results shed new light on customer valuation and market segmentation

Dynamic pricing with two revenue streams

We study casino revenue management through the pricing of hotel rooms in the presence of gaming revenue, which is random. We identify a stochastic order based on customers' gaming profiles, from which a monotonic inventory price of rooms is obtained. We develop a threshold-type pricing policy for a special customer segmentation scheme that allows customers' winning profiles to be ranked in terms of the failure rate order. Our results shed new light on customer valuation and market segmentation. (C) 2011 Elsevier B.V. All rights reserved

Monotone optimal control for a class of Markov decision processes

This paper provides a unified framework to study monotone optimal control for a class of Markov decision processes through D-multimodularity. We demonstrate that each system in this class can be classified as either a substitution-type or a complement-type system according to the possible transition set, which can be used as a classification mechanism that integrates a variety of models in the literature. We develop a generic proof of the structural properties of both types of system. In particular, we show that D-multimodularity is a generally sufficient condition for monotone optimal control of different types of system in this class. With this unified theory, there is no need to pursue each problem ad hoc and the structural properties of this class of MDPs follow with ease. (C) 2011 Elsevier B.V. All rights reserved