Wenhuang Liu

A framework for virtual enterprise operation management

This paper presents researches on operation management for virtual enterprises (VEs). A virtual enterprise is a temporary alliance of member enterprises (MEs) formed to exploit fast-changing opportunities. During the operation of a virtual enterprise, its constituent member enterprises, which are geographically distributed and organizationally independent, collaborate with each other to execute the whole business process (BP) of the virtual enterprise. With the aim of addressing business integration for virtual enterprises, this paper develops a framework for virtual enterprise operation management. From the viewpoint of business processes, carried out is integral research on business process modeling, analyzing, and managing for virtual enterprises. Both the distributed business process model and the model of the virtual enterprise itself are established. The former provides the functional basis of the virtual enterprise operation, while the latter provides its structural basis. Further, the two models are integrated through the loading from the distributed business process model to the virtual enterprise model. Through such model separation and integration, business process management for virtual enterprises is enacted and business integration for virtual enterprises is achieved.

Customer churn prediction using improved one-class support vector machine

Customer Churn Prediction is an increasingly pressing issue in todays ever-competitive commercial arena. Although there are several researches in churn prediction, but the accuracy rate, which is very important to business, is not high enough. Recently, Support Vector Machines (SVMs), based on statistical learning theory, are gaining applications in the areas of data mining, machine learning, computer vision and pattern recognition because of high accuracy and good generalization capability. But there has no report about using SVM to Customer Churn Prediction. According to churn data set characteristic, the number of negative examples is very small, we introduce an improved one-class SVM. And we have tested our method on the wireless industry customer churn data set. Our method has been shown to perform very well compared with other traditional methods, ANN, Decision Tree, and Naive Bays.

An application of the AHP in 3PL vendor selection of a 4PL system

As a fourth party logistics provider integrates the capacities of third party logistics providers, 3PL vendor selection is an important problem. Furthermore, 3PL vendor selection is a complex multi-criteria decision problem. The decision made by the decision maker or an evaluation team can be improved by a systematic and logistical approach to access priorities based on the inputs of the decision maker or the team made by several people. The analytic hierarchy process (AHP) can be very useful in reaching a likely result which can satisfy the decision maker or the team. In this paper, an AHP-based model is formulated and applied to a case study to examining the function in 3PL vendor selection. The use of the proposed model indicates that the computed quantitative evaluations can be applied to improve the precision of the selection.

Directed graph optimization model and its solving method based on genetic algorithm in fourth party logistics

Based on the introduction of the concept of the 4th party logistics and the decision supporting system in its operation, the directed graph model with multi dimension weight was established for its optimization problem of how to select the route, the transportation method and the third party logistics provider concurrently. Genetic Algorithm is used to solve this directed graph model. An adaptive length-variant coding method is employed to represent the individual. The initial group is generated at random. After crossover and mutation are done, individuals are selected according to the rank they obtain when comparison is taken in the sense of fitness, of course randomly and elitism is applied. The results of experiments show that this Genetic algorithm can help to get the optimal solution to the directed graph model and solve the optimization problem in the operation of 4th party logistics.

The decision optimization model of 4PL

With the Increased competition in the transport market, the new international logistics service provider must develop solutions tailored to meet the unique and special needs of each customer. Building upon the foundation of 3rd party outsourcing, 4PL emerges and acts as an electronic intermediator that connects suppliers, producers, carriers and customers to dynamic supply chain networks. Of such transportation networks the operative planning task of the hub-and-spoke network is a challenging task for the management. In particular, the transport management has to decide where all quantifies within the transportation network flow over the hub from or to the depots, or whether a hybrid hub-and-spoke network is preferred in which direct transports also take place. Upon these, Optimization model is studied and a 4PL optimization system for these operative planning tasks is developed and applied to a real case of a Chinese logistic service provider. The result of the case indicates that the model and algorithm presented in the paper can provide a reasonable supply chain scheduling scheme.

Petri-net-based business process modeling for virtual enterprises

The paper presents our studies on Petri net based business process modeling for virtual enterprises. A virtual enterprise (VE) is a temporary alliance of member enterprises. Generally, a business process consists of a series of logically interrelated activities, to which appropriate resources will be assigned. In the virtual enterprise, both the activities and the resources are in multiple member enterprises, while collaborations exist among these distributed activities and resource sharing is often required. Thus, the modeling of business processes in virtual enterprises is challenging work. Based on Petri nets, the paper proposes a business process modeling method for virtual enterprises, which focuses on the two basic elements of the business process: activities and resources, while addressing their properties of distribution and collaboration particular to virtual enterprises.

Artificial immune system for fraud detection

Credit card transactions continue to grow in number with the rapid growth of the electronic commerce, leading to a higher rate of stolen account numbers and subsequent losses by banks. Improved fraud detection thus has become essential to maintain the viability of the payment system. In this paper, we propose a case-based genetic artificial immune system for fraud detection (AISFD). It is a self-adapted system designed for credit card fraud detection. With the case-based learning model and genetic algorithm, the system can perform online learning with limited time and cost, and update the capability of fraud detection in the rapid growth of transactions and commerce activities.

Agent-based virtual enterprise modeling and operation control

We propose an agent-based virtual enterprise model and provide the agent collaboration mechanisms under the model, thereby achieving agent-based virtual enterprise modeling and operation control. We establish a network of distributed activity agents and resource agents for each member enterprise, collaborations among which can deal with activity precedence arrangements and activity-resource assignments in each sub-business-process. Then, we model each member enterprise in the virtual enterprise as an agent. Collaborations among member enterprise agents can deal with activity coordination and resource sharing among various sub-business-processes. Thus, our agent-based approach achieves distributed control over the whole business process execution of the virtual enterprise.

An agent-based approach for workflow management

The authors propose an agent based approach for workflow management, aiming at achieving flexible and dynamic workflow management in the distributed environment. We treat agents as autonomous entities with abilities to solve problems independently and propose an agent hierarchy as well as an agent model. The agent hierarchy consists of three kinds of agents at three neighboring levels: activity agents, role agents and actor agents. With our agent hierarchy, the gap between the dynamic workflow enactment and the static business process model can be bridged. The three levels of agents collaborate with each other through the contract-net approach and the feedback mechanism. Through such collaboration, activity-actor assignments can be achieved flexibly and dynamically; and the workflow execution can be monitored and managed in a real time fashion. The agent model consists of three sub-agents: a message-receiving one, a decision-making one and a message-sending one. Connected by two message queues, these three collaboratively operating sub-agents can complete functions of an agent effectively. Through message transfers of the message-receiving/sending sub-agents and the message based behavior-performing of the decision-making subagent, individual agents as well as the agent hierarchy can operate effectively and efficiently.

Applications of classification trees to consumer credit scoring methods in commercial banks

Based on the theory of classification trees, the samples that are taken out from one commercial bank of China are put into classification tree models. When comparing results of models, it is considered that the model size, the structure of the sample and error cost could influence models error rates. The optimized classification tree model is produced out based on the comparisons. It is concluded that classification trees are more suitable than logistic regression for present domestic credit scoring because of characters of the samples, through comparing classification trees and logistic regression.