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…     

A NOTE ON THE STOCHASTIC ROOTS OF STOCHASTIC MATRICES

In this paper, we study the stochastic root matrices of stochastic matrices. All stochastic roots of2×2 stochastic matrices are found explicitly.A method based on characteristic polynomial of matrix isdeveloped to find all real root matrices that are functions of the original 3×3 matrix, including allpossible(function)stochastic root matrices. In addition, we comment on some numerical methods forcomputing stochastic root matrices of stochastic matrices.     

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.     

ADVANCES IN DECISION ANALYSIS AND SYSTEMS ENGINEERING FOR MANAGING LARGE-SCALE ENTERPRISES IN A VOLATILE WORLD： INTEGRATING BENEFITS, OPPORTUNITIES, COSTS AND RISKS （BOCR） WITH THE BUSINESS MOTIVATION MODEL （BMM）

1. Introduction Recent advances in Information and Communication Technologies (ICT) have occurred in a number of areas includinginformation quality (Chutimaskul and Wangpipatwong 2004), strategy (Sha, Hung and Lin 2004) organization (Crowne 2004), technological change (Mitchell 2004), and utility1. Introduction Recent advances in Information and Communication Technologies (ICT) have occurred in a number of areas includinginformation quality (Chutimaskul and Wangpipatwong 2004), strateg…     

AN AHP MODEL FOR BRINGING EXPERTS TO CONSENSUS ON MEDICAL PAYMENT STANDARDS

1. Introduction Many countries with health insurance systems conduct periodic payment standardsadjustments. The main reasons are to address continually rising health care costs and to ensure an equitable allocation of resources. From the248 JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING data of the Organization for Economic Co-operation and Development (OECD) countries, the proportion of health care costs as a percentage of Gross Domestic Product (GDP) continues to r…     

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.     

ON IMPROVING AN INTEGRATED INVENTORY MODEL FOR A SINGLE VENDOR AND MULTIPLE BUYERS WITH A RELAXED MATERIAL ORDERING CYCLE POLICY

1. Introduction With the development of information technology and the increasing market competition, simultaneously reducing inventory costs of raw materials, work-in-process, and finished items in different stages has become a major focus for supply chain management. Industrial practice and academic research have shown that VMI (Vendor Managed Inventory) can improve supply chain performance by decreasing inventory levels and costs. VMI is a collaborative business initiative where the vend…     

ON INVENTORY STRATEGIES OF ONLINE RETAILERS

1.Introduction This research focuses on online retailers(etailers,hereafter)who engage in the sale of physical goods.In general,the order fulfillment process of such an etailer can be depicted by Figure1.As presented in Figure1,a customer will place an order at the etailer’s website.Upon receipt of each order,the etailer will confirm whether or not stock is available to fulfill the order.Assuming that inventory is indeed available,the order will be packaged,after which it will be delivered …     

CUSTOMER EQUITY： MAKING MARKETING STRATEGY FINANCIALLY ACCOUNTABLE

1. Introduction The long-term value of a firm is largelydetermined by the value of the company’scustomer relationships, which result in thefirm’s ‘customer equity’ (Blattberg andDeighton 1996), defined by Rust, Lemon andZeithaml (2000, p.4…     

Two-way road network design problem with variable lanes

This paper studies a new form of transportation network design problem. In urban transportation network, unreasonable phenomenon can occur in certain traffic period （e.g. on/off duty period）, which demonstrates that the flows of opposite directions on a two-way road are seriously asymmetric; one traffic link of a two-way road congest heavily but the other is hardly used. In order to reduce transportation congestion and make full use of the existing road resources, we propose a lane reallocating approach in peak period, and establish a discrete hi-level programming model for the decision-making. Then, based on particle swarm optimization （PSO） technique, a heuristic solution algorithm for the hi-level model is designed. Finally, the lane reallocating approach is demonstrated through a simple transportation network.     

Random evolving networks under the diameter and average connectivity constraint

In this paper, under the constraint that the average distance and the average degree （k） remain approximately constant, we studied a random scale-free network model. We found that, if the network maintains the form of its degree distribution and the maximal degree kc is N-dependent cutoff function kc（N）〈 N, the degree distribution would be approximately power-law with an exponent between 2 and 3. The distribution exponent has little relationship with the average degree, denoted by （k）. The diameter constraint can be interpreted as an environmental selection pressure, which could explain the scale-free nature of networks. The numerical results indicate that, under the diameter constraint, the preferential attachment can produce the cutoff function kc（N）〈 N and power-law degree distribution.     

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.     

Comparative analysis on traditional procurement and e-procurement strategy of supply chain

With increasingly intense competition between enterprises, the realization of advanced supply chain management has become an exquisite premise for the survival of firms. Procurement management is an important means to reduce costs and to enhance the competitive advantage. By exploiting the single period newsvendor model, this paper analyses and compares the benefit mechanisms of e-procurement and traditional procurement to quantify the effect of the Internet on supply chain procurement management in a neutral e-market. This work was partly supported by the National Natural Science Foundation of China under Grant No. 70125004 and 70572050. Guangshu Chang is a lecturer of Zhengzhou Institute of Aeronautics. He received his master degree from Zhengzhou University in 2000. His research interests include e-commerce, supply chain management and quality management. Jichao Xu is a professor of Zhengzhou Institute of Aeronautics. His research interests include quality management and quality engineering. Jianfeng Yang is a PhD student of Management School, Northwestern Polytechnical University. His research interest includes quality management. Jinfeng He is a PhD student of Management School, Northwestern Polytechnical University. Her research interest includes quality management. Li Zhang is a PhD student of Management School, Northwestern Polytechnical University. Her research interest includes quality management.     

A MODIFIED ANT-BASED TEXT CLUSTERING ALGORITHM WITH SEMANTIC SIMILARITY MEASURE

1. Introduction As an important application field of the data clustering technologies (Jain and Murty et al. 1999), text clustering is unsupervised partitioning of a collection of textual documents into self-similar groups so that any item is more similar with another item in the same group thanwith an item outside the group. Such groups are called clusters, which are run-timely formed during the clustering process, instead of being pre-defined as in the case of text categorization, which comm…     

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.     

AGENT-BASED SIMULATION FOR KANSEI ENGINEERING： TESTING A FUZZY LINEAR QUANTIFICATION METHOD IN AN ARTIFICIAL WORLD

This paper argues that agent-based simulation can be used as a way for testing Kansei Engineering methods which deal with the human reaction from sensory to mental state, that is, sensitivity, sense, sensibility, feeling, esthetics, emotion affection and intuition. A new fuzzy linear quantification method is tested in an artificial world by agent-based modeling and simulations, and the performance of the fuzzy linear method is compared with that of a genetic algorithm. The simulations can expand people＇s imagination and enhance people＇s intuition that the new fuzzy linear quantification method is effective.     

A COMPARATIVE STUDY OF DATA MINING METHODS IN CONSUMER LOANS CREDIT SCORING MANAGEMENT

1. Introduction Data mining (DM), sometimes referred to as knowledge discovery in database (KDD), is a systematic approach to find underlying patterns, trends, and relationships buried in data. Data mining has drawn much attention from bothresearchers and practitioners due to its wide applications in crucial business decisions. Basically, the research on DM can be classified into two categories: methodologies and technologies. According to Curt (1995), the technology part of DM consists of…     

Data crystallization applied for designing new products

It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable events. This is realized by data crystallization, where dummy items, corresponding to potential existence ofunobservable events, are inserted to the given data. These dummy items and their relations with observable events are visualized by applying KeyGraph to the data with dummy items, like the crystallization of snow where dusts are involved in the formation of crystallization of water molecules. For tuning the granularity level of structure to be visualized, the tool of data crystallization is integrated with human＇s process of understanding significant scenarios in the real world. This basic method is expected to be applicable for various real world domains where previous methods of chance-discovery lead human to successful decision making. In this paper, we apply the data crystallization with human-interactive annealing （DCHA） to the design of products in a real company. The results show its effect to industrial decision making.     

The M/M/1 queue with working vacations and vacation interruptions

In this paper, we study the M/M/1 queue with working vacations and vacation interruptions. The working vacation is introduced recently, during which the server can still provide service on the original ongoing work at a lower rate. Meanwhile, we introduce a new policy：, the server can come back from the vacation to the normal working level once some indices of the system, such as the number of customers, achieve a certain value in the vacation period. The server may come back from the vacation without completing the vacation. Such policy is called vacation interruption. We connect the above mentioned two policies and assume that if there are customers in the system after a service completion during the vacation period, the server will come back to the normal working level. In terms of the quasi birth and death process and matrix-geometric solution method, we obtain the distributions and the stochastic decomposition structures for the number of customers and the waiting time and provide some indices of systems.     

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.