Optimal Reinsurance Under Distortion Risk Measures and Expected Value Premium Principle for Reinsurer

This paper discusses optimal reinsurance strategy by minimizing insurer’s risk under one general risk measure:Distortion risk measure.The authors assume that the reinsurance premium is determined by the expected value premium principle and the retained loss of the insurer is an increasing function of the initial loss.An explicit solution of the insurer’s optimal reinsurance problem is obtained.The optimal strategies for some special distortion risk measures,such as value-at-risk(VaR) and tail value-at-risk(TVaR),are also investigated.     

Direction and polarization estimation for coherent sources using vector sensors

A two-dimensional direction-of-arrival (DOA) and polarization estimation algorithm for coherent sources using a linear vector-sensor array is presented. Two matrices are first constructed by the receiving data. The ranks of the two matrices are only related to the DOAs of the sources and independent of their coherency. Then the source’s elevation is resolved via the matrix pencil (MP) method, and the singular value decomposition (SVD) is used to reduce the noise effect. Finally, the source’s steering vector is estimated, and the analytics solutions of the source’s azimuth and polarization parameter can be directly computed by using a vector cross-product estimator. Moreover, the proposed algorithm can achieve the unambiguous direction estimates, even if the space between adjacent sensors is larger than a half-wavelength. Theoretical and numerical simulations show the effectiveness of the proposed algorithm.     

RETRACTION NOTE： EXPLORING THE VALUE OF INSTALLED BASE： PRICING INFORMATION GOODS UNDER VALUE DEPRECIATION AND CONSUMER SOCIAL LEARNING

The article Exploring the value of installed base： Pricing information goods under value depreciation and consumer social learning published in Volume 22, Issue 3, pages 362-382 by Yifan Dou and Tianliang Liu, has been retracted by agreement between the authors and the journal Editor-in-Chief. The core contributions in this article have been used without significant acknowledgement and approval by the project research team.     

Multi-Objective Optimization of Urban Bus Network Using Cumulative Prospect Theory

Multi-objective optimization of urban bus network can help improve operation efficiency of the transit system and develop strategies for reducing urban traffic congestion in China. The work used cumulative prospect theory, currently the most influential model for decision under uncertainty,to optimize urban bus network. To achieve the research objective, the work developed the theoretical framework of urban bus network optimization, including optimization principle, optimization objectives and constraints. Furthermore, optimization objectives could comprehensively reflect expectations of passengers and bus companies from the dimension of time, space and value. It is more scientific and reasonable compared with only one stakeholder or dimension alone in the previous studies. In addition,the technique for order preference by similarity to ideal solution(TOPSIS) was used to determine the positive and negative ideal alternative. The correlations between the optimization alternatives and the ideal alternatives were estimated by grey relational analysis simultaneously. The cumulative prospect theory(CPT) was used to determine the best alternative by comparing comprehensive prospect value of every alternative, accurately describing decision-making behavior compared with expected utility theory in actual life. Finally, Case of Xi’an showed that the method can better adjust the bus network,and the optimization solution is more reasonable to meet the actual needs.     

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors.The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables,and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model.Finally,a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example.The results show that the model has good effects for simulation and prediction.     

A hypersonic target coherent integration detection algorithm based on Doppler feedback

The traversal search of multi-dimensional parameter during the process of hypersonic target echo signal coherent integration,leads to the problem of large amounts of calculation and poor real-time performance.In view of these problems,a modified polynomial Radon-polynomial Fourier transform(MPRPFT)hypersonic target coherent integration detection algorithm based on Doppler feedback is proposed in this paper.Firstly,the Doppler estimation value of the target is obtained by using the target point information obtained by subsequent non-coherent integration detection.Then,the feedback adjustment of the coherent integration process is performed by using the acquired target Doppler estimation value.Finally,the coherent integration is completed after adjusting the search interval of compensation.The simulation results show that the algorithm can effectively reduce the computational complexity and improve the real-time performance on the basis of the effective coherent integration of hypersonic target echo signals.     

Setting the Optimal Exercise Prices of Executive Stock Options

Exercise-price policy is perhaps the central design issue regarding nontradable Executive Stock Options (ESO). In this paper, we give the value line of ESO, V(P), and the range of the incentive-maximizing exercise prices which is defined as the exercise prices that generate incentives, εn(P)/εP, within 1 percent of the maximum using the “certainty equivalence” approach, similar to that adopted by Richard Lambert et al.. Our results show that, holding constant the company‘s cost of making an option grant, incentives are maximized by setting exercise prices within a range that typically includes the grant-date market price.     

The generalized symmetric coalitional Banzhaf value for multichoice games with a coalition structure

With respect to multichoice games with a coalition structure,a coalitional value named the generalized symmetric coalitional Banzhaf value is defined,which is an extension of the Shapley value for multichoice games and the symmetric coalitional Banzhaf value for traditional games with a coalition structure.Two axiomatic systems are established：One is enlightened by the characterizations for the symmetric coalitional Banzhaf value,and the other is inspired by the characterizations for the Banzhaf value.     

Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

1. INTroDUCTIONFinancial institutes often hold asset portfolios consisting of bonds, stock, etc., whose values often vary due tothe change of market factors such as interest rate and exchange rate. The induence on the value of portfoliosmade by the bad variation of majrket factors is watched specially by the financial institutes. That is to say, it isnecessary to estimate the probability and degree of the decrease in the value of portfolios during a given timeperiod. As an integrated frame…     

Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.     

品牌体验价值对品牌资产影响的过程机理

品牌资产的提升是现代企业营销努力的重要目标之一,不同于以前研究者从营销组合变量出发,该研究基于消费者体验的视角,分析消费者品牌体验价值如何对品牌资产发挥作用;并加入消费者购买经历和卷入程度作为调节变量,观察不同购买经历和卷入程度水平下,品牌体验价值对品牌资产的影响作用的差异.实证结果表明:品牌体验价值的4个维度感官体验价值、情感体验价值、社会体验价值和知识体验价值对品牌资产的3个维度品牌忠诚、感知质量和品牌联想具有广泛的影响关系;同时,在不同的消费者购买经历和卷入程度水平下,其影响力的大小存在差异.     

Simulating the supply disruption for the coordinated supply chain

There are many disruptive accidents in the supply chain operations system and achieving the coordination of supply chain is main objective for supply chain research. While disruptive accidents have increasingly influenced the coordinated operation of the supply chain, existing research literature on the supply chain coordination is setting in a stationary environment. The answer for how the disruptive accidents affect the coordinated supply chain is given in this paper. Based on the benchmark supply chain which is coordinated by the negative incentive mechanism, we study the impacts of supply disruption on the supply chain system by using simulation approach in which two different distribution function of random variable are used to express the supply disruption. Comparison between these two simulation results and possible coordination mechanism under the supply disruption are proposed. From the perspective of supply chain risk management, we provide the inspiration for the manager.     

SERVICE VALUE NETWORKS： VALUE, PERFORMANCE AND STRATEGY FOR THE SERVICES INDUSTRY

1. Introduction The services industry provides services notgoods (Hughes and Mitchell et al., 1993). Thisindustry is moving towards globalization(Kathawala and Abdou, 2003). In 1870 theservice sector employed slightly more than 20%of the U.S.…     

MODELING JUMPS IN RETURNS OF FINANCIAL ASSETS AS M4 PROCESSES： MEASURED EXCHANGE RATE EXPOSURE OF ASIAN EQUITY PORTFOLIO

1. Introduction An early analysis of exchange rate changes and share prices found that the general stock market index tended to move up (down) immediately after a devaluation (revaluation) of the local currency (Giddy 1974). It is surprising that previous researches (Jorion 1990; Amihud 1993; Bodnar and Gentry 1993) find that no contemporaneous relationship between exchange rate changes and excess equity market returns of largest U.S. exporting firms. Recently, it has argued that there is a…     

Technical Note ：SINGLE-PERIOD TWO-PRODUCT INVENTORY MODEL WITH SUBSTITUTION： SOLUTION AND PROPERTIES

In this paper, we study a single-period two-product inventory model with stochastic demands and downward substitution. The optimal order quantities are presented and some properties are provided. Comparing with newsboy model, we prove that both the profit and the fill rate can be improved by using the substitution policy. This work was supported partly by NSFC/RGC Joint Research Program under grant 79910161987 and the National Science Foundation of China (79825102, 70231010, 70321001). Lianqiao CAI is lecturer of School of International Business, Beijing Foreign Studies University. He received his B.S. and M.S. from School of Economics and Management, Tsinghua University, in 1995 and 1998, and Ph.D of Management Science from Tsinghua University in 2002. His research areas include supply chain management, optimization techniques. Jian Chen is Professor and Chairman of the Management Science Department and co-director of the Research Center for Contemporary Management, Tsinghua University. He has over 80 papers published in some leading international journals and first class Chinese journals, and has been a principal investigator for over 20 grants or research contracts with National Science Foundation of China, governmental organizations, and companies. His main research interests include supply chain management, E-commerce, modeling and control for complex systems, decision support systems and information systems, and forecast and optimization techniques. He serves as associate editor of the “IEEE Transactions on Systems, Man and Cybernetics: Part A” and “IEEE Transactions on Systems, Man and Cybernetics: Part C”, and on the Editorial Board of “The International Journal of Electronic Business” and “System Research and Behavioral Science”. He is the recipient of the Outstanding Contribution Award of IEEE Systems, Man, and Cybernetics Society in 1996, and the Young Scientist Award of China in 1992. He was Secretary General of the 1996 IEEE International Conference on Systems, Man, and Cybernetics in Beijing, Co-chair of the IPC of 1998 International Conference on Systems Science and Systems Engineering, Chair of the First Asian eBiz Workshop in 2001, Co-chair of the Asian eBiz Workshop in 2002 and 2003, and Co-chair of the international conference on Global Supply Chain Management in 2002. Houmin Yan received his B.S. and M.S. from the Department of Automation, Tsinghua University, in 1982 and 1985, respectively, and his Ph.D. from the Faculty of Management, University of Toronto in 1993. From Jan. 1994, he is with the Department of Systems Engineering and Engineering Management, the Chinese University of Hong Kong as an Assistance, Associate and Full Professor. He was a tenured Associate Professor at School of Management, the Univ. of Texas at Dallas. His main research areas are operations management, stochastic models, simulations, and supply chain management. He has published in journals such as Operations Research, Manufacturing and Service Operations Management, Production and Operations Management, Journal of Optimization: Theory and Applications, IIE Transactions and IEEE Transactions. He consults several high-tech companies, such as Motorola, C&K Systems, and Oriental Power, on issues spanning from production planning and scheduling, supply chain management to business process re-engineering. He is a member of INFORMS.     

生活方式、顾客感知价值对中国消费者购买行为影响

主要研究生活方式直接或通过顾客感知价值间接对中国消费者购买行为的影响.选择手机作为研究对象,上海作为样本的选择地点,在问卷调查的基础上,借助探索性因子分析和确认性因子分析,获得生活方式、顾客感知价值2个度量量表.随后,用结构方程对生活方式、顾客感知价值与中国消费者购买行为之间的关系进行了研究.发现:生活方式直接影响消费者购买行为,间接通过顾客感知价值影响消费者购买行为.最后,提出了一个基于生活方式和顾客感知价值的市场划分方法,帮助企业针对消费群体定位、设计、生产、完善产品和实施有效的市场营销策略.     

A perishable inventory system with service facilities, <Emphasis Type="Italic">MAP</Emphasis> arrivals and <Emphasis Type="Italic">PH</Emphasis> — Service times

We consider a continuous review perishable （s,S） inventory system with a service facility consisting of a waiting hall of finite capacity and a single server. We assume two types of customers, ordinary and negative, arrive according to a Markovian Arrival Process （MAP）. An ordinary customer joins the queue and a negative customer instead of joining the queue removes one ordinary customer from the queue. The removal rule adopted in this paper is RCE （removal of a customer from the end）. The individual customer＇s unit demand is satisfied after a random time of service which is assumed to have a phase-type distribution. The life time of each item and the lead time of the reorders have been assumed to be independent exponential distributions. The joint probability distribution of the number of customers in the system and the inventory level is obtained for the steady state case. Various stationary system performance measures are computed and the total expected cost rate is calculated. The results are illustrated numerically.     

Expert discovery and knowledge mining in complex multi-agent systems

Complex problem solving requires diverse expertise and multiple techniques. In order to solve such problems, complex multi-agent systems that include both of human experts and autonomous agents are required in many application domains. Most complex multi-agent systems work in open domains and include various heterogeneous agents. Due to the heterogeneity of agents and dynamic features of working environments, expertise and capabilities of agents might not be well estimated and presented in these systems. Therefore, how to discover useful knowledge from human and autonomous experts, make more accurate estimation for experts＇ capabilities and find out suitable expert（s） to solve incoming problems （＂Expert Mining＂） are important research issues in the area of multi-agent system. In this paper, we introduce an ontology-based approach for knowledge and expert mining in hybrid multi-agent systems. In this research, ontologies are hired to describe knowledge of the system. Knowledge and expert mining processes are executed as the system handles incoming problems. In this approach, we embed more self-learning and self-adjusting abilities in multi-agent systems, so as to help in discovering knowledge of heterogeneous experts of multi-agent systems.     

A situation calculus based approach to dynamic management of e-business services

In the era of e-businesses, the traditional business services are greatly challenged by the ever-increasing demands from customers with various backgrounds and personalities. Large numbers of new e-businesses are driven by the needs of customers. The existing dynamics inherent in the customer needs require the corresponding dynamic management of services. Attempting to respond to customers in a rapid and intelligent way, this paper proposes a situation calculus based approach for dynamically managing e-Business services in the ubiquitous environment. By employing the formalism of the situation calculus to enable intelligence and automation, the approach can implement. the functions of service automatic composition and model verification. These functions will improve the degree of customer-orientation and enable fast responsiveness in the emerging e-service systems.     

A NESTED PARTITIONS FRAMEWORK FOR SOLVING LARGE-SCALE MULTICOMMODITY FACILITY LOCATION PROBLEMS

Large-scale multicommodity facility location problems are generally intractable with respect to standard mixed-integer programming (MIP) tools such as the direct application of general-purpose Branch & Cut (BC) commercial solvers i.e. CPLEX. In this paper, the authors investigate a nested partitions (NP) framework that combines meta-heuristics with MIP tools (including branch-and-cut). We also consider a variety of alternative formulations and decomposition methods for this problem class. Our results show that our NP framework is capable of efficiently producing very high quality solutions to multicommodity facility location problems. For large-scale problems in this class, this approach is significantly faster and generates better feasible solutions than either CPLEX (applied directly to the given MIP) or the iterative Lagrangian-based methods that have generally been regarded as the most effective structure-based techniques for optimization of these problems. We also briefly discuss some other large-scale MIP problem classes for which this approach is expected to be very effective. This work is supported partly by the National Science Foundation under grant DMI-0100220, DMI-0217924, by the Air Force of Scientific Research under grant F49620-01-1-0222, by Rockwell Automation, and by John Deere Horicon Works. Leyuan Shi is a Professor of the Department of Industrial Engineering at University of Wisconsin-Madison. She received her Ph.D. in Applied Mathematics from Harvard University in 1992, her M.S. in Engineering from Harvard University in 1990, her M.S. in Applied Mathematics from Tsinghua University in 1985, and her B.S. in Mathematics from Nanjing Normal University in 1982. Dr. Shi has been involved in undergraduate and graduate teaching, as well as research and professional service. Dr. Shi’s research is devoted to the theory and applications of large-scale optimization algorithms, discrete event simulation and modeling and analysis of discrete dynamic systems. She has published many papers in these areas. Her work has appeared in Discrete Event Dynamic Systems, Operations Research, Management Science, IEEE Trans., and, IIE Trans. She is currently a member of the editorial board for Journal of Manufacturing & Service Operations Management, is an Associate Editor of Journal of Discrete Event Dynamic Systems, and an Associate Editor of INFORMS Journal on Computing. Dr. Shi is a member of IEEE and INFORMS. Robert R. Meyer received a B.S. in Mathematics from Caltech and an M.S. and a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. He is currently Professor of Computer Sciences at the University of Wisconsin-Madison, where he has been on the faculty since 1973. He has co-edited six volumes of optimization conference proceedings and written more than 80 articles focusing on areas such as nonlinear network optimization, parallel decomposition algorithms for large-scale optimization, genetic algorithms, and theory and applications of discrete optimization. Mehmet Bozbay is a research assistant in the Department of Industrial Engineering at University of Wisconsin-Madison. He is currently working towards his Ph.D. degree in Industrial Engineering. He received M.S. degrees in Industrial Engineering and Computer Sciences from University of Wisconsin-Madison, and a B.S. degree in Mathematics from Beloit College. He has been dealing with real-life supply chain optimization problems for the last 4 years. He is a member of INFORMS. Andrew J. Miller is an Assistant Professor of the Department of Industrial Engineering at the University of Wisconsin—Madison. He received his Ph.D. in Industrial Engineering from the Georgia Institute of Technology in 1999, his M.S. in Operations Research from the Georgia Institute of Technology in 1996, and his B.S. in Mathematics from Furman University in 1994. Dr. Miller has been involved in research, undergraduate and graduate teaching, and professional service, as well as in some software prototyping and development. Dr. Miller’s research focuses on theoretical and computational aspects of mixed integer programming, and on its application to areas in production planning, supply chain design, and other fields. He has published several papers in these areas, including articles in Mathematical Programming, Operations Research, and European Journal of Operations Research. He has refereed numerous articles for the journals mentioned above, as well as for Management Science, Annals of Operations Research, and others. Dr. Miller is a member of INFORMS and of the Mathematical Programming Society.