Biying Shou

An expected regret minimization portfolio selection model

Fuzzy portfolio selection has been widely studied within the framework of the credibility theory. However, all existing models provide only concentrated investment solutions, which contradicts the risk diversification concept in the classical portfolio selection theory. In this paper, we propose an expected regret minimization model, which minimizes the expected value of the distance between the maximum return and the obtained return associated with each portfolio. We prove that our model is advantageous for obtaining distributive investment and reducing investor regret. The effectiveness of the model is demonstrated by using an example of a portfolio selection problem comprising ten securities in the Shanghai Stock Exchange 180 Index.

Managing supply uncertainty under supply chain Cournot competition

We study the Cournot competition between two supply chains that are subject to supply uncertainty. Each supply chain consists of a retailer and an exclusive supplier which has random yield. We examine how the levels of supply uncertainty and competition intensity affect the equilibrium decisions of ordering quantity, contract offering, and centralization choice. We show that a retailer should order more if its competing retailer’s supply becomes less reliable or if its own supply becomes more reliable. A supply chain with reliable supply can take great advantage of the high supply risk of its competing chain. Furthermore, for decentralized chains we characterize the optimal wholesale price contracts with linear penalty, under different supply risks and competition scenarios. Finally, we show that supply chain centralization is a dominant strategy, and it always makes the customers better off. Nevertheless, if the supply risk is low and the chain competition is intensive, centralization could actually decrease the supply chain profit, compared with the case where both chains do not choose centralization. This results in a prisoner’s dilemma. On the other hand, if the supply risk is high and/or the competition level is low, centralization always increases the supply chain profit. The desirability of supply chain centralization is enhanced by high supply uncertainty or low chain competition.

Pricing and effort investment for a newsvendor-type product

We investigate a dominant retailer’s optimal joint strategy of pricing and timing of effort investment and analyze how it influences the decision of the manufacturer, the total supply chain profit, and the consumers’ payoff. We consider two pricing schemes of the retailer, namely, dollar markup and percentage markup, and two effort-investment sequences, namely, ex-ante and ex-post. A combination of four cases is analyzed. Our results show that: (1) under the same effort-decision sequence, a percentage-markup pricing scheme leads to higher expected profit for the retailer and the whole supply chain, but a lower expected profit for the manufacturer and a higher retail price for the consumers; (2) under the same markup-pricing strategy, the dominant retailer always prefers to postpone her effort decision until the manufacturer makes a commitment to wholesale price, since it can result in a Pareto-improvement for all the supply chain members. That is, the retailer’s and manufacturer’s expected profits are higher and the consumers pay a lower retail price; and (3) among the four joint strategies, the dominant retailer always prefers the joint strategy of percentage-markup plus ex-post effort decision. However, the dominated manufacturer always prefers the joint strategy of dollar-markup plus ex-post effort decision, which is also beneficial to the end consumers.

Serial Agile Production Systems with Automation

To gain insights into the design and control of manufacturing cells with automation, we study simple models of serial production systems where one flexible worker attends a set of automated stations. We (a) characterize the operational benefits of automation, (b) determine the most desirable placement of automation within a line, and (c) investigate how best to allocate labor dynamically in a line with manual and automatic equipment. We do this by first considering two-station Markov decision process models and then studying three-station simulations. Our results show that the capacity of production lines with automatic machines can be significantly lower than the rate of the bottleneck. We also show that automating a manual machine can have a dramatic effect on the average work-in-process (WIP) level, provided that labor is the system bottleneck. Once a machine becomes the bottleneck, the benefits from further automation are dramatically reduced. In general, we find that automation is more effective when placed toward the end of the line rather than toward the front. Finally, we show that automation level increases the priority workers should give to a station when selecting a work location.

Optimal pricing for local and global WiFi markets

This paper analyzes two pricing schemes commonly used in WiFi markets: flat-rate pricing and usage-based pricing. The flat-free pricing encourages users to achieve the maximum WiFi usage and targets at users with high valuations in mobile Internet access, whereas the usage-based pricing is flexible to attract more users - even those with low valuations. First, we show that for a local provider, the flat-rate pricing provides more revenue than the usage-based pricing, which is consistent with the common practice in todays local markets. Second, we study how Skype may work with many local WiFi providers to provide a global WiFi service. We formulate the interactions between Skype, local providers, and users as a two-stage dynamic game. In Stage I, Skype bargains with each local provider to determine the global Skype WiFi service price and revenue sharing agreement; in Stage II, local users and travelers decide whether and how to use local or Skype WiFi service. Our analysis discovers two key insights behind Skypes current choice of usage-based pricing for its global WiFi service: to avoid severe competition with local providers and attract travelers to the service. We further show that at the equilibrium, Skype needs to share the majority of his revenue with a local provider to compensate the local providers revenue loss due to competition. When there are more travelers or fewer local users, the competition between Skype and a local provider becomes less severe, and Skype can give away less revenue and reduce its usage-based price to attract more users.

Pricing for Local and Global Wi-Fi Markets

This paper analyzes two pricing schemes commonly used in Wi-Fi markets: the flat-rate and the usage-based pricing. The flat-rate pricing encourages the maximum usage, while the usage-based pricing can flexibly attract more users especially those with low valuations in mobile Internet access. First, we use theoretical analysis to compare the two schemes and show that for a single provider in a market, as long as the Wi-Fi capacity is abundant, the flat-rate pricing leads to more revenue. Second, we study how a global provider (e.g., Skype) collaborates with this monopolist in each local market to provide a global Wi-Fi service. We formulate the interactions between the global and local providers as a dynamic game. In Stage I, the global provider bargains with the local provider in each market to determine the global Wi-Fi service price and revenue sharing agreement. In Stage II, local users and travelers choose local or global Wi-Fi services. We analytically show that the global provider prefers to use the usage-based pricing to avoid a severe competition with the local provider. At the equilibrium, the global provider always shares the majority of his revenue with the local provider to incentivize the cooperation. Finally, we analytically study how the interaction changes if the local market has more than one local provider. In this case, the global provider can integrate the coverages of multiple local providers and provide a better service. Compared to the local monopoly case, local market competition enables the global provider to share less revenue with each of the local providers. However, we numerically show that the global providers revenue could decrease, as he shares his revenue with more providers and can only charge a lower price.

Train Rescheduling With Stochastic Recovery Time: A New Track-Backup Approach

Train rescheduling is an important decision process in railway management. It aims to minimize the negative effects arising from the disturbances via real-time traffic management. Two main challenges are how to formulate the dynamic and complex rescheduling problem as an optimization model, and how to obtain a good solution within a short time limit. Focusing on the stochastic capacity recovery times of blocked tracks, we propose a new track-backup rescheduling (TBR) approach which optimally assigns each affected train a backup track, based on the estimation of recovery time, the original timetable, and track changing cost. Then, we formulate a mixed integer programming (MIP) model to obtain a conflict-free timetable which minimizes the delay cost and the expected track changing cost. A greedy algorithm is designed to reorder trains and reschedule the arrival and departure times, and then we use an MIP algorithm to solve the optimal track backup strategy. Based on the Beijing-Shanghai high-speed railway line, we conduct extensive experimental studies which show that the TBR approach can reduce the rescheduling cost by an average of 10.17% compared with traditional approaches. More important, the greedy-based algorithm is shown to be able to obtain good solutions (with an average error of only 2.85%) within 1.5 s, which implies the high potential of our approach in a real-time traffic management system where fast response is critical.

Task aware information access for diagnosis of manufacturing problems

Pinpoint is a promising first step towards using a rich model of task context in proactive and dynamic IR systems. Pinpoint allows a user to navigate decision tree representations of problem spaces, built by domain experts, while dynamically entering annotations specific to their problem. The system then automatically generates queries to information repositories based on both the users annotations and location in the problem space, producing results that are both task focused and problem specific. Initial feedback from users and domain experts has been positive.

Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

Dynamic spectrum access is a new paradigm of secondary spectrum utilization and sharing. It allows unlicensed secondary users (SUs) to exploit the opportunistically underutilized licensed spectrum. Market mechanism is a widely used promising means to regulate the consuming behaviours of users and, hence, achieve the efficient allocation and consumption of limited resources. In this paper, we propose and study a hybrid secondary spectrum market consisting of both the futures market and the spot market, in which SUs (buyers) purchase underutilized licensed spectrum from a spectrum regulator (SR), either through predefined contracts via the futures market, or through spot transactions via the spot market. We focus on the optimal spectrum allocation among SUs in an exogenous hybrid market that maximizes the secondary spectrum utilization efficiency. The problem is challenging because of the stochasticity and asymmetry of network information. To solve this problem, we first derive an off-line optimal allocatio...

Equilibrium contracting strategy under supply chain to supply chain competition

We consider two competing supply chains, each consisting of one dominant supplier and one retailer. The supplier offers either a consignment contract or a wholesale-price contract. If the retailer accepts the contract, she then decides the stocking level and the retail price of the product. The demand for each product is stochastic and price-sensitive. We show that the equilibrium contract strategy depends on the price sensitivity of the demand and the cost-share rate of the retailer. More specifically, for symmetric supply chains, we observe that consignment contract is the equilibrium strategy of the two supply chains when (1) the retailers cost-share rate is large, or (2) the retailers cost-share rate and price sensitivities are small; otherwise, wholesale-price contract is the equilibrium strategy of the two supply chains.