This paper reviews the work of financial system engineering in China from 2010 to 2014, and further concludes future development strategies. Firstly, the research object and method are defined. Through literature documentation process with both China and abroad papers, statistics of Journals, research institutions, research team, and supported fund are obtained. Through Bradford and Lotka test, we conclude the current research status of financial system engineering development in China. Further, all research are classified into 9 main research questions, which are the key research questions during the past 5 years. Finally, we proposed development strategies for future development of financial system engineering research.
After the initiation of carbon trading pilots in seven provinces and cities in China, issues of their effectiveness and impact on economy, environment and export are of great significance to policy makers, managers and experts of environmental science. To respond to these issues, we first define the concepts of carbon emission reduction, energy saving and low-carbon economy and discuss policy measures and economic instruments related to carbon emission reduction. Focusing on "quantity control" and "price control", we analyze in detail their implementation process and actual effectiveness in both theoretical and practical points. Also, we present in this paper the mechanism and pathways of carbon emission reduction and their inspiration to China from macro, micro and technical perspectives. We then review the related literature and comment how these academic results can be used to help China to achieve its carbon reduction target at optimal economic costs. Finally, we point out the deficiencies and possible theoretical gaps in the previous studies and present some important issues that need further academic exploration.
Hesitant fuzzy linguistic term set (HFLTS) is defined as an ordered and consecutive subset of the linguistic term set for a linguistic variable. This paper carries out some states of the art review over the development of HFLTS theory. Firstly, we introduce the definition and originality of the HFLTS, and then conduct the review from four aspects, which are the hesitant fuzzy linguistic fusion theory, the hesitant fuzzy linguistic measurement theory, the hesitant fuzzy linguistic preference relation theory and the hesitant fuzzy linguistic decision making methodologies. Finally, we outline the future research directions on qualitative decision making with hesitant fuzzy linguistic information.
In recent years, a novel application domain of scheduling, namely carrier-based aircraft deck operation scheduling is emerged. As an unexplored domain of scheduling, carrier-based aircraft deck operation scheduling has attracted more and more attention from both academic and industrial experts in the filed of scheduling, control theory and operations research et al. In this paper, a survey of carrier-based aircraft deck operation scheduling problem is presented both at home and abroad. Firstly, the carrier-based aircraft deck operation scheduling problem is formulated as a fundamental mixed integer programming mathematical model; secondly, a comprehensive review at abroad is given, which mainly focuses on United States; thirdly, four related topics of carrier-based aircraft deck operation scheduling at home are classified, including system simulation, system design, system optimization, and route planning. Finally, we conclude this survey with future trends and further research directions. This study aims to promote theoretical research and engineering applications of carrier-based aircraft deck operation scheduling problem at home.
Based on the definition of systemic linkages, we employ the asymmetric CoVaR approach to estimate the systemic linkages between each Chinese bank and the Chinese banking system and the systemic linkages between two individual Chinese banks. We show that the systemic linkages in the Chinese banking system have asymmetric properties, thus we use the asymmetric CoVaR approach to reestimate the systemic linkages in the Chinese banking system. Our approach can be used to identify the systemically important banks in China and to assess the systemic risk spillovers in the Chinese banking system. Furthermore, we find that the determinants of the two kinds of systemic linkages are some bank characteristics, such as total loans, common equity, retained earnings and so on. These measures of systemic linkages serve as useful additional toolboxes to both bank supervisors and bank managers.
Based on five original sentiment indicators in Hong Kong stock market, including the closed-end fund discount rate, the average first-day returns of initial public offering (IPO), the number of IPO, the market trading volume and turnover, this paper uses the principal component analysis method to calculate a comprehensive investor sentiment index. After excluding the trend and seasonal factors from the comprehensive investor sentiment index and Hong Kong Hang Seng Index by autoregressive moving average-generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) family models, this paper makes correlation analysis and Granger causality test on the residuals of ARMA-GARCH model. The study shows that ARMA-GARCH models can effectively process the autocorrelation and heteroscedasticity of investor sentiment index and Hong Kong Hang Seng Index. Also, it indicates that the Hang Seng index return is the Granger cause of investor sentiment in short terms while not in long terms. That is to say investor sentiment would be more optimistic in short terms when the Hong Kong stock market goes up, and vice versa.
In this paper, we discuss the financial crisis contagion from developed markets to Asian emerging markets. We propose a new framework that includes: noise extraction method, noise correlation analysis and asset portfolio noise decomposition method. The empirical analysis shows that, there is a significant contagion effect from developed markets to emerging markets during the U.S. subprime crisis in 2007. The contagion effect from Hong Kong market is largest compared with other developed markets. The contagion from Singapore market has a time-varying feature, and the contagion from Japan to neighboring emerging markets is decreasing. Due to the existence of contagion effect, it is difficult to divert risk by using portfolio investment strategies.
Predicting tourism traffic accurately plays an important role in making policies for tourist administration. It helps to distribute the resources reasonably and avoid the tourism congestions. To improve the tourism prediction accuracy, this study considered the noise interference and proposed a forecast model of CLSI-EMD-BP using web search data. This model firstly applied CLSI to combine the web search data into a search index, then it denoised the series with EMD. EMD extracted the high frequency noise from the original series. The low frequency series of search index would be used to predict the low frequency tourism series. Taking Jiuzhaigou as an example, this study trained the model and predicted the next 22 weeks tourism arrivals. The conclusion demonstrated that the forecast error of CLSI-EMD-BP model is lower remarkably than the baselines of time series model, the web search data model and the BP network model. This revealed that nosing processing is necessary as well as CLSI-EMD-BP forecast model can improve the prediction accuracy.
As a kind of capital, intermediate inputs play an important role that cannot be ignored in the process of production. Their coefficient size reflects a country's economic growth mode. Current mainstream economic growth theories only consider the value added production function, rather than gross output production function, thus ignoring the role of intermediate inputs in the production process and the evaluation of economic efficiency. This paper is based on the statistical characteristics, basic model and empirical test of the basic paradigm. From the perspective of statistical characteristics, China's intermediate inputs coefficients are significantly higher than that of U.S. and Japan and other developed countries. The energy consumption per unit GDP is far over the world average level, which shows that the characteristic of China's economic growth is of extensive growth mode. By using theoretical derivation and numerical simulation, this paper has drawn the conclusion that a country's economic growth mode is related to the intermediate inputs elasticity of substitution, value added rate (VAR), technical level, and some other parameters. Firstly, there exists substitution rather than complementary linkage between primary investment and intermediate inputs. Secondly, economic growth rate shows negative correlation with the size of the elasticity of substitution of intermediate inputs, and the greater, the slower, and vice versa. Thirdly, inverted U shape shows that with the increase of intermediate inputs rate, the equilibrium output increases first and then decreased. In other words, there exists an optimal VAR. In the empirical analysis by using data of China, U.S., Japan and Brazil, the paper proves that there are obvious differences in the elasticity of substitution of intermediate inputs among different countries at their different stages during development. On the one hand, there is a different elasticity of substitution at different stage for a country with a certain independence, and the elasticity of substitution of U.S. is much higher than that of China. On the other hand, there is deviation between the actual VAR and the optimal VAR among these countries, and the deviation of China and Brazil is much larger than that of U.S. and Japan.
Based on the barycentric rational interpolation, we propose a new model to fit the term structure of interest rates, which include construction of basis function, parameter estimation, knot selection and model forecasting. Compared with the traditional models, the new model has at least four advantages. Firstly, it has higher smoothness in fitting interest curve. Secondly, it has lower computational complexity in estimating parameters. Thirdly, it has richer economic significance of estimation parameters. And lastly, it has higher prediction accuracy. Our empirical results are based on the term structure of treasury bills in Shanghai Stock Exchange, and the results show that the new model not only has better performance in structure analysis, computational complexity, prediction capability and economic significance, but also improve the fitting and pricing accuracy of bonds.
Effective government regulation is an important approach to control food safety incidents. In this paper, we establish a symmetric game model to study the strategy choice of food enterprises under government participation, explore government regulation failures with the number of food enterprise increases. The research suggests that when the number of food enterprises increases on the market, the border earnings of non-self-discipline enterprises increase, more enterprises becomes non-self-discipline and provide unsafe food production; that is the reason why the fixed checking probability of government cannot adapt to the market situation where many food enterprises coexistence. In the game, inspect frequency of government, cost of self-discipline and punishment of non-self-discipline are the most important for enterprise which could affect the choice of behavior. In order to cope with the failure of the government regulation effectively, the government should increase inspect frequency, reduce the cost of self-discipline, and increase the punishment of non-self-discipline.
This article establishes an integrated credit decision optimization model based on the geometric Brownian motion theory, which takes discriminatory pricing, performance probability, demand shifting and the probability of business opportunities into account. The model also launches a new credit decision rule. Empirical results show that it is conducive to improve the estimation accuracy of total revenue by using the different risk premium standards, the probability of business opportunities and demand shifting of different credit ratings after choosing credit sale, which provide the date basis for choosing the timing of credit; The improved rule of credit opportunity selection provides a direct simple method to calculate the optimal time, which overcomes the limitations of the traditional comparison method.
Vertical integration not only generates vertical economy but also engages the vertically integrated provider (referred as VIP hereafter) into sabotaging the independent enterprise in the downstream market. For example, the VIP may lower the quality of the intermediate product, delay the shipment, and hide key information. The recent cases such as the discrimination in broadband market and LCD panel monopoly are typical evidence of the VIP's sabotage behavior. Using mathematical modeling and simulation which is based on data from China Uni-com broadband market, we analyze the factors that lead to sabotage and the mechanism behind. The results show: First, VIP's sabotage is increasing with the final product's price, yet decreasing with the intermediate product's price. Second, VIP's sabotage is decreasing with the independent enterprise's market share. Third, VIP's sabotage is decreasing with the subsidiary's other elements cost and increasing with independent enterprises' other element cost. Fourth, only within a certain range, sabotage is negatively related to the price elasticity of independent enterprise and positively related to the cross price elasticity between subsidiary and independent enterprises. Beyond this certain range, it's difficult to judge the relation between sabotage and elasticity. These findings provide theoretical guidance for policy making in deterring sabotage and regulation.
To reduce the decay of perishable products in the process of production and delivery, it is necessary to appropriately arrange the production and delivery of perishable products subject to their deadlines. Therefore, to minimize the total operational costs of producing and delivering perishable foods, an optimization model was developed for joint production-delivery problem with time-windows, by considering the time-dependent characteristics of road networks in real world. According to the characteristics of the model, a hybrid genetic algorithm was proposed and validated by using a numerical experiment. The results show that the time-dependent characteristics of road networks have a remarkable impact on customer service level. The total operational costs and the loss of product value can be reduced further by optimizing the number of delivery vehicles in use.
For considering the role of both online social network and offline social network in the public opinion transmission, the multilayer synchronization network containing media layer, online layer and offline layer was built. And on this basis, public opinion simulation system framework was set up. Based on the research achievements of predecessors for human social network structure, multi-level synchronous network is given in the default setting. Through case simulation, demonstrated the mutual influence between online and offline networks and compared the different effect of the number of witness in the self-media communications and multimedia communications in the role of public opinion propagation. In the end, discussed the compatibility and scalability of the multilayer synchronous network model and put forward the improvement and extension direction.
Organizational learning from rare events has been a new branch in the field of organizational learning in recent years. However, organizations have paid most of their attention to the single rare event at present and neglected the internal associations of present event with relevant events happened previously. In fact, the superposition of relevant rare events can strengthen the problems contexts so that organizations can enhance the effectiveness of organizational learning from rare events through improving the quality of organization attention. Therefore, this study tested the relationships between the quality of organization attention in the specific problems context and the effectiveness of organizational learning from rare events based on the data about the accidents of American airline companies in a period of 20 years from the perspectives of stability and vividness. Specifically, the influence of attention stability on the effectiveness of organizational learning can be indicated by the results that the higher the frequency of relevant rare events and the greater the intervals between previous relevant rare events and present rare event, the higher the effectiveness of organizational learning would be. The influence of attention vividness on the effectiveness of organizational learning can be reflected by the U-shaped relationship between the vividness of the reasons behind all rare events occurring within industries and the effectiveness of organizational learning and the inversed U-shaped relationship between the vividness of the reasons behind all rare events occurring within organizations and the effectiveness of organizational learning.
In this paper, we introduce scheduling problems with time-dependent linear deteriorating jobs and position-dependent exponential learning effects under group technology. In our model, the group setup times are linear functions of their starting times and there is linear deterioration and exponential learning effect with processing time of jobs. We show that the problems to minimize the makespan and the sum of completion times remain solvable in polynomial, respectively.
This paper focused on hazardous materials vehicle scheduling between multiple routes. A mixed integer programming model was formulated to maximize profit and minimize the risk cost of the densely populated area, and the effect of limited capacity of vehicle and scheduling cost was involved explicitly. The main decisions were determining transportation price and vehicle scheduling. Using hierarchical solving method, we presented optimal vehicle quantity without generalized allocating cost and time constraints to allocating capacity firstly. Then, a search procedure was put forward to check the feasibility of it to time constraints, and optimal vehicle quantity that satisfied to time constraints was given, which is proved at mathematics. Finally, on this basis the search mechanism was revised to calculate the minimum of generalized vehicle allocation cost. The validity of it was verified by the numerical examples. Compared with the case that there is no vehicle allocating between different routes, the model with vehicle scheduling could reduce transportation price and increase realized demands.
To study on pedestrian behavior and simulate pedestrian walking trajectory quantitatively, a pedestrian behavior model based on nested logit (NL) and cross nested logit (CNL) model is proposed. At first, starting from the modeling approaches, basic theories of behavior theory, NL model and CNL model are analyzed emphatically. Then, in the model, pedestrians are divided into two types of free flow and non-free flow. Different functions are built for the five willingness of keeping direction, toward destination, speed changes, avoiding opposite pedestrian and transcend the pedestrian in same direction, respectively. Furthermore, the NL and CNL model of pedestrian walking behavior is proposed. Finally, the software of biogeme is applied to calibrate the coefficients of the model using the data tracked in the video, and the model results are compared with the real trajectory data to validate the accuracy of the model. Accuracy of the model is 80.26\%. The results show that, the built discrete choice model can simulate the real walking trajectory in the low-density situation with high accuracy.
In rough set model, α quantitative indiscernibility relation is a generalization of both strong and weak indiscernibility relations. However, such three indiscernibility relations based rough sets do not take the test costs of the attributes into consideration. To solve this problem, a test-cost-sensitive α quantitative indiscernibility relation based rough set is proposed. From the viewpoint of the binary relation, the new rough set is then sensitive to test costs. Moreover, the relationships among strong, weak, α quantitative and test-cost-sensitive α quantitative indiscernibility relations based rough sets are explored. Finally, it is noticed that the traditional heuristic algorithm does not take the decreasing of cost into account. Therefore, not only a new fitness function is proposed, but also such fitness function is carried out in genetic algorithm for obtaining reduct with minor test cost. The experimental results show that such approach not only decreases the uncertainty comes from boundary region, but also decreases the cost of reduct.
Haze has brought great harm to human daily life, so it is very important to analyze the factors which influence the haze badly. Starting from one-dimensional cellular automata (CA) and the drawbacks of the traditional method，a novel BGSO algorithm with weak-link Coevolution mechanism (CWLBGSO) combine with Rough Set is introduced in this paper. In CWLBGSO, the whole search space was divided into several sub-spaces, and each sub-space has a subpopulation, then after several iterations, suboptimum in each subpopulation will perform crossover operation to keep the dynamic diversity. After that CWLBGSO combined with rough set is applied to forecast the key factors which influence haze badly. The datasets of Beijing, Guangzhou and Shanghai are used to conduct experiments, also 10-fold and SVM is involved to analyze the classification accuracy and influence factors, the experimental results show that our method can effectively eliminate redundant factors, also has relatively higher stability and credibility.
This paper presents an improved chaos invasive weed optimization algorithm for solving the multi-objective permutation flow shop scheduling problem, minimizing the maximum completion time (makespan), total flowtime (TFT) and total tardiness simultaneously. In this study, the grey entropy correlation grade based on entropies weights is adopted for adaptive value distribution strategy. Then, a fast non-dominated sorting approach is introduced to establish external archive. In addition, evolutionary population updates are combined with chaos search around the optimal location to maintain external archive, which improves the efficiency of the scheduling algorithm. Finally, typical OR-Library examples are selected to test the new method. Numerical results demonstrate the effectiveness of the designed algorithm compared with NSGA-Ⅱ.
In recent years, as the real estate prices continue to rise rapidly, the problem of the residents' housing increasingly prominent. In order to alleviate the housing problems of low-income residents, the government built a large number of indemnificatory communities. However, the configuration problem of public service facility is widespread imperfect, and the supply is lag and inefficient or excess, which leads to the process of population check-in is slowly and low occupancy rate. The situation affects the quality of residents' life, also the realization of indemnification and the harmonious society building. Taken a Shanghai indemnification community as an example, the paper built the particle swarm optimization (PSO) models that can clearly express the space of supply for indemnificatory community public service facility under the condition of multi-objective constraint. Besides, in order to improve community public service facility configuration to be scientific and rational, also to perfect the configuration theory of community public service facilities and achieve the best use of public service facility, the paper empirical analyzed affordable community public service facilities configuration optimization simulation and application of research strategy, which has a certain theoretical and practical significance.