The traditional parameter analysis method would bring the diversity of results in analysis. Starting directly from the actual transaction data, the subdominant ultra-metric space of a precise topology sequence was proposed. Via date data from the most representative 52 stock index July 22, 2005 to June 30, 2009, September 15, 2008 was as the cutoff point before and after the financial crisis. The results: there was more significant clustering effect in geographical regions of stock index after the outbreak of financial crisis; degree of relevance is significantly increased and the linkage was strong among stock index; the dynamic stability of the global stock market overall was relatively stable. The influence of American stock index reduceed, but it of China was growing after the financial crisis. In order to avoid sharp fluctuations in the stock market, financial supervision should be global coordination, and should not be a country or a region of isolated acts. The diversity of the world stock market should be maintain, to prevent economic and financial integration of the saying "One with all, a loss will also be ruined".

This paper studies pricing decisions in a two-echelon dual-channel supply chain wherein a manufacturer sells products through a direct online store beside an existing retail channel. The purpose is to investigate the interaction between the manufacturer and the retailer in order to find out the role and impact of direct channel. We consider both the purchasing cost and acceptance level of customers in each channel. The demand of both channels is derived from a consumer utility and selection model. The pricing equilibriums are obtained and the manufacturer's pricing strategies are analyzed when wholesale price is exogenous. We find out that the role of direct channel is multifold: 1) the direct channel can extend the manufacturer's market, satisfying more customers' demand beside the retailer's market segment; 2) it can pose an underlying threat to the retailer and thus make the retailer lower the market selling price. In the end we analyze the channel structure selection problem when the manufacturer has the right to set wholesale price. This paper may be used as a reference for companies involved with direct online channels.

The coordination problem of a supply chain with one supplier and $n$ Bertrand competing retailers was analyzed. It was proved that a revenue sharing contract can be used to coordinate the supply chain under normal environment. But the coordination may be broken off by demand scale and cost disruptions, and the optimal strategies that the centralized decision-making supply chain replied to the disruptions were proposed by solving the Kuhn-Tucker (KT) condition of optimal profit of supply chain system under disruptions. It was further proved that an improved revenue sharing contract can be used to coordinate the decentralized decision-making supply chain when demands and costs were disrupted simultaneously. Finally, a numerical example was presented to illustrate the efficiency of the proposed model.

With the use of SFA and the C-D production function, and models respectively for the nation and three regions, the author analyzes the regional characteristics of production efficiency of various regions in China and the influence factors of production efficiency. The empirical results show that the regional pattern of production efficiency: Eastern > Central > West; the regional characteristics of the change rate of production efficiency: Central > West > East, the gap between Central and West with Eastern is narrowing; All models consistently show that openness and effective and efficient use of infrastructure all have general positive effect on productive efficiency; Optimum of industrial structure has the most significant effect on marginal productivity to Eastern & West; while the role of technological innovation is most prominent for Central.

Time, cost and quality are three basic objectives in engineering project management. They are interacting with each other. Taking time, cost and quality into account systemically is significant for project decision-maker to management and control project. In this paper, project quality is measured through a quality measurement system. According to Pareto optimal theory, a computation procedure is designed based on genetic algorithms and Pareto ranking, thus the time-cost-quality trade-off model is built. The optimal resource utilization options can be obtained from Pareto solutions calculated by this model. At the end of this paper, a case study is given to verify the feasibility and practicability of the mode1.

Industrialized agriculture covers agricultural production, processing, sales and services, with labor-intensive characteristics, to attract nearby peasant an important carrier of employment income. In this paper, agricultural resources, market demand as the basic constraints, through the establishment of multi-objective, nonlinear, dynamic optimization model, examining the expansion of job opportunities for agricultural laborers through industrialized operation of agriculture. Studies have shown that the adoption of the agricultural industrial chain to extend the vertical and horizontal combinations, to increase job opportunities for the agricultural labor force, effective way to avoid the labor gap in busy seasons and the serious issues such as idle in slack seasons, so that agricultural resource can be effectively used, the rural labor forces can do more farm work to increase their income, the agricultural investors can gain much more return, witch will be beneficial to the rural labor force and the agricultural investors.

Based on the analysis of movie life cycles in Chinese movie market, this article establishes the Gamma demand model considering seasonal factor and other influence factors,and studies movie audience population and the decay situation combining with variable intercept model in panel data model and multiple regression model. The result shows that the model could more accurately reflect the audience population change rule in domestic movie market. In addition, in view of Chinese movie market, quantitative study has been carried out in order to make clear how the factors such as movie stars, sequel, budget etc. affect the audience population, what help the movie policy-maker make some instructions to formulate strategies as well as the audience demand forecasts. Empirical study shows the necessity of considering seasonality. In addition, We find large amount of audiences can cause the audience decay rate to appear quicker, in fact the difference of the decay rate between big budget and small budget movies is very small, which is different from some other literatures, and a simulation indicates our conclusion is reasonable.

In 1962, Wu and Jiang introduced the notion of essential equilibrium points and essential games for n-person noncooperative finite games and proved that every finite game can be closely approximated by an essential game. And in 1963, Jiang introduced the notion of essential components of the set of equilibrium points for n-person noncooperative finite games and proved that there exists at least one essential component of the set of equilibrium points for every finite game. These are the important contributes of Chinese mathematicans for game theory.

This paper considers a class of Job-Shop scheduling problem abstracted from the seamless steel tube production, which is characterized by finite buffer storage, flexible routes for every job, transform times between jobs and multi-objective of scheduling. We formulate it with mixed-integer- programming model. Given the problem is of NP-hard, improved genetic algorithm is suggested, then local search algorithm is presented based on it. We test and compare the performance of proposed algorithms, whose effectiveness can be well verified in scheduling decision support system for the production of seamless steel tubes of real company.

This paper used fuzzy mathematics method to study random service system. That is called fuzzy random service system. Then authors applied the fuzzy structured element theory to analyze fuzzy random service system. The complicacy and infeasibility of fuzzy number's operation based on Extension Principle in tradition analysis of fuzzy random service system is overcome availably. This method can provide abundant information for managerial decision. Then new mart supermarket is empirical researched based on this models. After comparing the result of traditional random service system and fuzzy random service system, it gets some important information.

This paper studies on the decision model of grey target, and defines the ideal optimization scheme is the positive clout and the ideal inferior scheme is the positive clout of the grey target. This paper comprehensively considers the optimization and the positive off-target distance, and base on the spatial analysis, defines the comprehensive off-target distance. Base on the size of the comprehensive off-target distance and the uncertainties of the index weights, this paper established a model of goal programming, and the gets the index weights by solving the model. Then the decision model of grey target with both the positive clout and the negative clout is established. Finally, the method is proved feasibly and effective through an example.

The model of grey incidence determines the closeness degree from the closeness and similarity of statistical sequence's geometrical form. Traditional grey incidence model calculates statistical sequence's correlation degree from perspectives of its acreage, slope, changing velocity, etc. These incidence models have dual influences exerted by horizontal and vertical coordinates that is amplitude and interval. Subsequently, inference of other factors occurs when we analyze the relationship between statistical sequence's individual factors. To overcome this limitation, the author put forward the amplitude correlation model and drew the conclusion that the model is in reference to the magnitude and direction of the wave amplitude, but is independent of its sequence distance, and that it can show the positive-negative relevance. This model was then applied to carry out a research into the relationship between add or subtract argument of the general domestic product of China and the household consumption expenditure, which comes out to be an effective one. The model applies to analyze two distinct wave sequence's data.

Space based early-warning is the monitoring and predicting process with the property of the discrete time sequence. Many decision-making factors, optimization objective functions and constraint conditions need be considered when scheduling the sensor tasks, as a result, the intelligent optimization algorithm is typically adopted to solve this nonlinear optimization problem. However these optimization methods are convergence to the Pareto solution in probability within the specified time. Three respects of work are done in this paper, firstly, the Decision Tree is applied to mine the heuristic knowledge; secondly, the Smoothed Naive Bayes is presented in order to provide the multi-class Decision Tree; finally, the heuristic knowledge is fused into the intelligent optimization algorithm, where local search operator is added. The experiment shows that Immune Colonal Selection increases 10.1% in terms of convergence probability, and Gene Algorithm increases 9.8%.

In view of the limitations of LEM2 algorithm, to improve the quality and efficiency of rule induction, improved LEM2 rule induction algorithm is proposed. Based on generalized decision, minimal- rule-first strategy is given, which can make rule more laconic and improve the quality of rule induction. Redundancy attribute-value pair set is defined, by deleting the redundancy attribute-value pair from the candidate attribute-value pair sets, which can accelerate convergence rate and improve the efficiency of rule induction. The experimental results show that the improved LEM2 algorithm is more effective for rule induction from incomplete information system.

To alleviate data sparsity and scalability issues of collaborative filtering technique in recommendation systems, a new hybrid collaborative filtering model based on Principle Component Analysis and Self-Organizing Map cluster method was proposed. In our approach, dimension reduction technique was first performed on whole data space. The clusters were generated from relatively low dimension vector space transformed by the first step, and then used for neighborhood selection in stead of searching in the whole user space, which can reduce the computation complexity in online recommendation. The experiments were based on web log data from E-government portal web site, and the results indicate that the proposed algorithm can provide better prediction accuracy compared with some exiting collaborative filtering algorithms.

The paper presented a distributed data mining model based on Support Vector Machines DSVM. It described the definition of multi-branches tree of Eigen (ET) and the method of building ET based on mobile Agents accessing to distributed datasets. It elaborated the concept by using ET to reflect the characteristic of attribute in the distributed dataset, and then proposed the algorithm of distributed incremental Support Vector Machines based on hull vector (HDIS) using the data structure of ET and the feature of Support Vector Machine. Finally, the ET was modified and improved by HDIS to realize distributed data mining. The experimental results show the DSVM providing high capability and efficiency of distributed business data mining.

Against the shortness of general steganalysis method which use the orthogonal wavelet to extract the characteristics, a effective steganalysis method based on wavelet package decomposition (WPD) and genetic algorithm was designed. Firstly, by three scales of WPD, image and its prediction-error version were decomposed into some coefficients subbands, the multi-order characteristic function (CF) moments of histogram were extracted from these subbands. Then genetic algorithm (GA) was employed to search and identify the potential informative features combinations for classification. The classification accuracy from the support vector machine classifier is used to determine the fitness in genetic algorithm. The experiments works on mixed image library, constituting by Outguess, F5, MB1 stego-images and cover images. Results show the method can detect stego and original images reliably, and the average detection accuracy of this method exceeds those of its closest competitors by at least 1.7% and up to 17.8%.

In order to ensure information security in an e-commerce business process, the article analyzed the characteristics in information security of e-commerce work, including confidentiality, integrity, authenticity, flexibility, legitimacy, effectiveness, and so on, and analyzed its impact on the quality of the requirements of e-commerce practitioners. The article built the quality index system including morality, intelligence, attitude, qualifications, personality, body structure and other aspects, and employed the fuzzy mathematical models and the Delphi method to determine the grade and weight of evaluation of the various projects and their indexes of the evaluation. Finally, it established and analyzed a comprehensive evaluation matrix of the quality of practitioners of information security in e-commerce to help businesses identify and select the outstanding staff in line with the qualifications of the functions of information security in e-commerce.

In 2009, Park, et al. proposed an efficient remote user authentication protocol. They claimed that their protocol was the first password and smart card based remote user authentication scheme which can resist the off-line password guessing attack, and had many advantages over existing solutions such as no password tables and timestamp, low communication and computational costs. However, this paper shows that their protocol cannot resist the forgery attack and off-line password guessing attack. To overcome the security weaknesses, two improved schemes based on either nonce or timestamp without affecting the merits of the Park, et al. scheme are proposed. Technical discussions are provided to show that the improved protocol is secure, efficient and practical.

Since complex networks have been extensively studied, we introduced the complex network theory to study the virtual community network evolution of the BBS. Firstly, we built the directed virtual community network through data information in BBS plate, and then studied the evolution of network topology characteristics with time, including the addition of the number of nodes and edges, power-law index of network's degree distribution and network's structural entropy. We discovered that evolution process of the network is from "orderly" to "disorderly" and then to "stable and orderly" state, and the existence of rich-club phenomenon in the community network. Then, based on evolution of virtual communities in the BBS plate, we proposed a virtual community network construction model. Simulation results show that its performance is similar to that of the virtual community network in BBS, which can explain the evolution of virtual communities to some extent, and is consequently of strong practical significance.

To solve the sequencing problem in multi-stage automotive assembly shops, the colour batch size constraints of paint shop and the spacing constraints emanating from the assembly shop are explicitly discussed. The spacing constraints are proved to be a sufficient condition for the capacity constraints. On the basis of those, the spacing constraint inequalities with utility workers and without utility workers are presented respectively. An integer programming model is presented where the cost of setups and the cost of utility workers are to to be optimized simultaneously. For computing conveniently with the optimal software, some nonlinear constraints in the model are transformed into linear constraints. Simulation results confirm the feasibility and validity of this proposed method.

To allocate capability scientifically and make best use of slot resources, an Arrival-Departure Ground Delay Programs under Collaborative Decision Making (CDM ADGDP) was brought forward. A multi-objection optimization model was proposed to allocate arrival-departure capability and slot. The model took the dynamic characteristics of airport capacity because of weather and also considered connecting flights and their influence. The model took the arrivals and departures as two interdependent processes, took Efficiency-Equity (E-E) as criterion based on arrival-departure capability trade-offs. Based on Ration-By-Schedule (RBS), arithmetic of Arrival-Departure RBS (AD-RBS) was presented for the case that arrivals and departures are two independent processes. With a multi-objective genetic arithmetic and data from an airport in China, the model was verified that it can not only use capability dynamically and fully, but also allot slots effectively and fair.

To allocate capability scientifically and make best use of slot resources, an Arrival-Departure Ground Delay Programs under Collaborative Decision Making (CDM ADGDP) was brought forward. A multi-objection optimization model was proposed to allocate arrival-departure capability and slot. The model took the dynamic characteristics of airport capacity because of weather and also considered connecting flights and their influence. The model took the arrivals and departures as two interdependent processes, took Efficiency-Equity (E-E) as criterion based on arrival-departure capability trade-offs. Based on Ration-By-Schedule (RBS), arithmetic of Arrival-Departure RBS (AD-RBS) was presented for the case that arrivals and departures are two independent processes. With a multi-objective genetic arithmetic and data from an airport in China, the model was verified that it can not only use capability dynamically and fully, but also allot slots effectively and fair.

The paper proposes cellular automaton (CA) model under the frication interference in mixed traffic condition. The model is built on NS model with a slowdown rule showing that motor vehicles slow down under the frication interference of bicycles. With various motor vehicle densities and bicycle densities, the simulation results of this model are consistent to the real situations. The results show that under the interference of bicycles, the average capacity of motor vehicle has decreased by 20% while its average velocity has decreased by 18%. Moreover, data from real observation and measurement also demonstrate validity and reliability of this model.

According to the theories of water rights, water market, game analysis and genetic algorithm, builds the game analysis model of secondary water distribution, solves the problem of regional water resources allocation in water rights trade model and administrative intermediation dispatch model, describes the secondary water distribution modeling approach and method based on game analysis theory, promotes water savings deeply used and regional interests to maximize in competition mode, improves genetic algorithm`s coding schemes, fitness function and crossover operator according to the characteristics of model equations, realizes model solution oriented to water rights transfer optimization. The results show that the model effectively resolve the profit equilibrium question between suppliers and users, optimizes the regional secondary water distribution, and provides reference for the managers of water resource.

Using Box-Cox technique in the estimation of hedonic housing price models, the log-likelihood ratio test and Theil inequality coefficient test for out-of-sample forecast was applied to the choice of an optimal functional form. The empirical results exhibit Box-Cox model superiors to linear, semi-log and log-log function form.

This paper discusses the optimal allocation of checkers when the product returns and demands are dependent, and the returned products must be checked before reselling. Supposing that the demands on every period are definite, the products can only be sent back during current period, the sojourn time of the products in the market and check time of the returned products both are exponentially distributed, the checkers will automatically adjust the checking speed according to the number of return products in the system, we take the number of checkers $n$ as the inventory control policy, and establish a costs control model by using finite source queuing theory. The problem is to determine the optimal $n^*$, such that the expected total costs are minimized when the system can't reach steady state in a finite period.

Service provider's work effort and customer's participation will decide the final output of the outsourcing service project, but the intangibility and unverifiability of their contributed resources will result in double moral hazard. Based on the problem that the formal outsourcing contract cannot incent simultaneously the effort of service provider and customer, a relational outsourcing contract is designed with principal-agent theory, then the incentive effect of the relational contract is analyzed. The conclusions indicate that customer' revenue and system profit under the relational contract are not less than that under the formal contract for all discount rate; the incentive effect of the relational contract increases with the discount rate increasing. When the discount rate is large enough, the first best outcome can be achieved through the relational contract. At last, a numerical example is provided.

The purpose of the study is to estimate the dynamic process of the basis change of agricultural futures. Since futures price equals to the unbiased estimation of spot price under the expectations theoretical framework, the relationship between basis and spot price can be identified by the state space model. In this study, basing on the seasonal and mean-reversion nature of agricultural price, the state transition equation of spot price is initially established. The measurement equation of basis is deduced under the framework of expectations theory. Then the state space model is constructed, through which the dynamic process of basis change is inferred from the information provided by spot price. At the end of the paper, an empirical research on the futures basis change of strong gluten wheat in CZCE is presented.

To improve individual customer churn prediction accuracy, integrated model of SMC, rough sets (RS) and least squares support vector machines (LSSVM), i.e., SMC-RS-LSSVM, for E-business customer churn prediction was proposed in this paper. Firstly, customers' active probabilities were obtained by using SMC model to identify customer churn status with the threshold of 0.5. The training and testing samples were formed by the correctly identified customers and incorrectly identified customers respectively. Then the attributes were reduced using rough sets and LSSVM was trained with training samples. Lastly, the trained LSSVM model was used to identify customer churn status of testing samples. Taking 2525 customers in an E-shop as samples, empirical results show that, compared with SMC, BP neural network and LSSVM models, integration model of SMC-RS-LSSVM is an efficient and practical tool for E-business customer churn prediction of testing samples.

Under the "Fact-Value" analytical paradigm of mass unexpected emergency, the paper builds the game equilibrium evolutionary model considering the mental models that reflect cognition structure different among grass-roots, higher-level government and social vulnerable group, which bases on the ideas of Akihiko and Masahiro, Liu and Xu. It analyzes applicable conditions of two government emergency management models between "grass-roots government resorts to police" and "higher-level government intervention", and the game equilibrium evolutionary direction and influencing factors.

The need to solve the emergency decision problems has been urgent nowadays due to its importance to help government in promoting social development and maintaining social stability. Several novel concepts, including department cooperative network, cooperative matrix, and cooperative coefficient, are proposed by considering the demands from multi-divisional cooperation and dynamic decision. Then an emergency decision model with multiple stages, multiple objectives, and multidivisional cooperation has been developed in the framework of multi-objective optimization. The main advantage of this model is that it can integrate the suggestions from different departments and can adjust decision dynamically according to the real-time situation. Further simulation experiments demonstrate that the model has great significance for the practical emergency decision problems and can accomplish scientific decision.

On the basis of fuzzy granular space, structural clustering analysis based on fuzzy proximity relations is proposed. Firstly, the concept of consistent clustering according to metric is proposed, and the research on consistent clustering of a fuzzy granular space is given. Secondly, the granular representation on structural clustering of a fuzzy proximity relation is studied, and the algorithm to obtain its structural clustering is given. Thirdly, the research to determine the optimal clustering based on a fuzzy granular space from a fuzzy proximity relation is proposed, and a new method to obtain it is given, which the new method is overall. Finally, the fusion technology is attained by applying the intersection operation of two fuzzy proximity relations. These conclusions provide a comprehensive theoretical tool and methodologies for studying structural analysis of complicated systems.

Factor state vector is transferred into quantifier guided order index vector by applying Borda function and linguistic quantifier. With the quantifier guided order index vector, a kind of new encouraging state variable weight vector is presented. Therefore, a variable weight averaging operator based on linguistic quantifier is constructed. In order to verify the capability of reflecting the linguistic value's semantics, some variable weight averaging operators based on several typical linguistic quantifiers and the corresponding OWA operators guided by the same linguistic quantifiers are compared. Finally, an example is presented.

To solve the problem that decision makers have bounded rational characteristics under uncertainty, two reasonable propositions are introduced, i.e., probability weights (PW) are invariable and outcome values (OV) are fuzzy. In terms of these propositions, two level decision making models and related theorems for deriving the optimal OV and PW are presented via balancing both levels' satisfactions, besides two level interactive decision making approach employed to rank decision making alternatives bounded rationally is also proposed. A simulation case shows the proposed approach is scientific, reasonable, and well applicable.

A quality performance (QP) assessment model and indicators based on ISO9004 standard are set up. Aimed at the characteristics of multi-levels, multi-indicators and the uncertainty of information in QP assessment, the evidential reasoning (ER) approach based on D-S theory is applied to QP assessment, the uncertain or unknown information in QP assessment are dealt with by using of the methods of fuzzy comprehensive judgment and group decision technique, and the computing methods of mass function are presented. A revised ER approach based on D-S theory in multiple-attribute decision-making under uncertainty is applied to the synthesizing of multi-experts and multi-indicators. Then a valid technique is established for the measurement and assessment of QP under uncertainty. Finally, a case is discussed to demonstrate the practicality and effectiveness of the method proposed in this paper.

The shortages of existed score function for the multi-criteria fuzzy decision making issue of the fuzzy environment are pointed. According to the size of the relationship between membership non-membership of vague sets and the partition of the set that is composed of vague value, the new methods are provided. They are called score function method and weighted score function method. The weight of criteria is also denoted by vague set. This method provides a effective tool for decision-makers.

In order to solve the difficult problem that unexpected events, which may make the original schedule infeasible, occur occasionally in container terminals, a disruption management model for berth and quay crane scheduling was developed by the methodology of disruption management. This model measured disruptions from three aspects: Operation cost, vessel delay cost and schedule deviation. To solve the disruption management model, a simulation optimization approach was proposed, and algorithms based on local rescheduling and tabu search were designed. Finally, numerical experiments were provided to illustrate the validity of the proposed model and algorithms. Results indicate that local rescheduling based algorithm can improve the computation efficiency comparing to full rescheduling based algorithm. Moreover, the disruption management model considers the benefit of different parties, thus increases the scientific of disruption recovery schedule.

The dispatching of disrupted airline schedules is a very complicated real-time network optimization problem, which belongs to NP-complete problem. Considering the situation caused by both the shortage of aircraft resources and the closure of airports, this paper adopts time-space network technique to construct the recovery network for each aircraft. Based on this, the problem is considered as a multi-commodity integer minimum cost flow with the side constraints, so a mathematic model of multi-commodity network flow is established. Column generation methods are introduced to solve this large integer programming problem, and the branch and bound algorithm is used to handle the non-integer solutions. Finally, a given instance analyzed in details validates the correctness and efficiency of the method.