The positive feedback trading phenomenon is significant in Chinese market, and buying-winners effect is much stronger than selling-losers effect. We call it rise-favor asymmetry of positive feedback trading. This paper studies if this rise-favor asymmetry has asset pricing power. This paper constructs reversal factor, positive feedback factor, and rise-favor asymmetry factor based on Fama-French three factor, and uses a sample that spans from Jan 1998 to Oct 2016 and contains daily data of all A shares that become a listed company before 2010 to do empirical tests. The paper finds that, the performance of rise-favor asymmetry factor is quite different from that of positive feedback factor and reversal factor; Although these three factors all have some pricing power individually, the pricing power of positive feedback factor and reversal factor is weak in the multi-factor pricing model, and only rise-favor asymmetry factor can significantly promote the pricing power of multi-factor model; The pricing power of rise-favor asymmetry factor does not result from price-rising chasing behavior, price-dropping chasing behavior, liquidity risk premium, or investor sentiment. In sum, rise-favor asymmetry is a new pricing factor that different from traditional factors, and its pricing power may relate to the market's compensation on the risk of irrational speculation.

This paper attempts to consider and solve the problem for companies to choose the optimal strategic route of green transformation technology investment based on economic fluctuation and their own situation. We apply a real option to conduct scenario analysis on the forecast economic development status and technology and get the optimal investment rules and the optimal choice route of the green transformation technology. The main results are:1) the initial role of carbon trading price is to promote the green transformation of high-energy enterprises; 2) enterprise's financial strength is an another important factor that influences green transition success and route selection for enterprise; 3) the key factors which influence green transition success and route selection for enterprise are the degree of economic prosperity, the height of the investment of the discount rate, and the development level of the green transformation technology. Furthermore, our theoretical model implicates that government should control the stability and prosperity of the economic environment and provide a good carbon trading mechanism and encourage to cultivate high green transformation technology with the high discount rate investment.

This paper extends the unified GARCH-Itô model proposed by Kim and Wang (2016) and introduces a more general method to model volatility with the combination of high-frequency and low-frequency data. The new method embeds a low-frequency GARCH structure into high-frequency volatility in a more flexible way, thus embraces a broader application. Theory and simulation study found good asymptotic property and finite sample performances of the quasi-maximum likelihood estimators proposed. In an empirical study, this new method was used to improve the bulk volume classification (BVC, Easley et al.(2013, 2016)). As a result, market participants' trading intentions were estimated more precisely.

Currently, there exists three kinds of steel trading markets in China:Spot market, futures market and B2B electronic trading market (Abbreviated as e-market). Do they reflect the steel market price common factor well? How about their dynamic evolution in terms of price discovery? These questions become hot point of steel producers, sellers, arbitrageurs, as well as market policy planners. In the light of vector error correction and conditional heteroscedasticity model, and analyzing the effects of past information to multiple dynamic conditional covariance matrix, this paper constructs time-varying information shares model based on two-dimensional and three-dimensional VECM-DCC-GARCH model to study the dynamic performance of steel markets in the long interval price discovery function. Empirical results of the daily data indicate that e-market exhibits greatest ability in incorporating information effecitively before hot roll bars futures established. After hot roll bars futures established, three kinds of steel market all contribute to the price discovery process. Most of the time, spot market leads the price discovery process, followed by the futures market and e-market. The role of e-market in price discovery is somehow considerable, while its role on price discovery evolves follower from dominator. In terms of steel markets in China, trading volume, margin level and liquidity have no obvious directly relationship with price discovery function.

Online portfolio selection is one of the fundamental problems in the field of computational finance. As financial markets are changing rapidly, investors need to dynamically adjust asset positions according to various kinds of information related to the capital market. Online portfolio strategy with side information is studied without probability assumptions on the asset prices. By using the relative entropy function to measure the distance between two portfolios, an online portfolio exponential gradient strategy with side information is proposed, and moreover it is proved a universal portfolio, i.e., its average growth rate is asymptotically the same as that of the best state constant rebalanced portfolio, which is offline. The strategy is tested on actual stock data, and the effect of transaction costs on the strategy is also analyzed, which the results show that this strategy can obtain higher returns.

In view of development lag has become the core factor to limit the efficiency of housing supply. Inspired by the continuous upgrading of domestic land leverage, we try to verify the mechanism of land leverage and development lag. We first use real option model to establish a more practical double stochastic differential equation and partial equilibrium model shows that when the market expectation is stable, the land development cycle is mainly determined by the land lever (i.e. the ratio of land price to housing price). In the past 2002-2015 years, the panel data regression of 31 provinces in China showed that, after controlling the external factors such as population density effectively, on average, the land leverage increased by 100 percentage points, and the development lag increases 20 percentage points. This conclusion is still stable after the test of the time trend, the impact of exogenous events and the location of the region. Then, the three stage mediating effect is established, and the overall mediating effect is 46% with the promotion of land leverage, the direct cost effect has become the main way to influence housing price compared with the indirect way of development lag. At the same time, there is a similar accelerator effect in land leverage, that is, with the improvement from lower to higher level, the positive spillover effect of land leverage on housing prices is stronger, and the effect is increased by about 80%. The study highlights the importance of structural reforms from the land supply side which implies the importance of effective management of development lag as well as land leverage in the overall policy framework of real estate regulation.

This paper selected the evaluation method of prospect theory as comprehensive evaluation method of evaluating Shanghai housing security policy effect, and then screened the corresponding evaluation index by means of correcting total correlation coefficient and factor analysis, thus laying the theoretical foundation for the scientific evaluation of Shanghai housing security policy effect. After model calculation had been done using the index data from 1998 to 2014, the change law of the comprehensive value estimating housing security policy effect was cleared, and the effects and function of various security housing policy was clarified. However, when compared with the inverted U-shaped development process of social security level, the exploration of multi-level housing security system is found to be relatively fallen behind for Shanghai.

Based on expected utility theory, the paper established a decision model for private sectors under social risks in PPP projects, in which private sectors' decision-making behavior was divided into positive one and negative one. Through discussion analysis, the paper summarized private sectors' social risk decision-making into four scenarios, where the private sectors must choose negative behavior in the case that private sectors fully bear the costs to deal with social risk. To resolve the problem, corresponding compensation mechanisms were put forward to ensure the positive behavior can be determined by private sectors under the four scenarios and improve the social efficiency of the PPP projects. In addition, the influence of long-term and short-term benefits as well as the contract period of PPP projects on social risk decision-making behavior was discussed in the paper. The conclusion can be drawn that the private sectors' attitudes to the long-term and short-term benefits are critical to determine the decision-making behavior. Moreover, partnerships and reasonable risk sharing is the effective approach to determine the positive behavior.

This paper studies a supply chain with one supplier and one buyer and explores the effect of complete inspection, sampling inspection, batch sampling inspection and combination strategy on the product quality control based on newsvendor model considering quality uncertainty and inspection error in decentralized and centralized supply chain. The results show that the increase of defective rate will reduce the retailer to order products, but will increase the order quantities and profits of the retailer under the combination strategy; and it is beneficial for the retailer under the complete inspection strategy in the centralized supply chain. Through comparative analysis of strategies:in the decentralized supply chain, if the defective rate is low, batch sampling strategy is optimal, but the combination strategy will be better with the improvement of the defective rate; in the centralized supply chain, the complete inspection strategy will be better. In addition, the selection of retailer quality control strategy is influenced by many factors, and the optimal strategy is not the same, but these factors will not change the trend of retailers' profits to change with the defective rate.

In the case that promotional local advertising of retailers undermine customer loyalty and reduce brand image. In order to analyze prerequisites that manufacturers carried out collaborative advertising in a cost-sharing form, and impacts of cooperative advertising on consumer demand and supply chain profits. Two competitive supply chains which were consist of single manufacturer and single retailer as the object of this paper. The Nash game model between supply chains and the Stackelberg game model with retailers as leaders were built. Cooperative advertising and non-cooperative advertising games in two sales cycles were compared and analyzed by considering long-term effects of advertising. The results show that prerequisites for manufacturers to cooperate advertising are obviously negative effect of advertising and high commodity substitution rate. When the commodity substitution is not obvious, cooperative advertising can effectively increase demand, on the contrary, the demand is reduced. Cooperative advertising does not improve retailer revenue. However, the incomes of manufacturers and total profits of supply chain are improved when the commodity substitution rate is low. The findings have a certain guiding significance to decision making of supply chain member on the local advertising practice.

Based on the evolutionary game method, influences of the costly second-party punishment mechanism on the equilibrium selection of the public goods game and the cooperative behavior of the population are investigated. The strategy evolution process of the population is described as a multidimensional Markov process. The evolutionary stable states of the system are analyzed based on the limit distribution of the stochastic process. Two kinds of punishments are considered respectively in this paper, namely, first-order punishments that only punish the defectors and second-order punishments that not only punish the defectors but also the cooperators who have not punished the defectors (second-order defection). The study reveals that compared with the first-order punishment, the second-order punishment mechanism can promote the evolution of cooperation within a larger parameter range. The system has critical values of punishment parameters for choosing different equilibrium results. The results are also compared with those of the corresponding deterministic replication dynamic model.

This paper proposes a competition and cooperation relationship model between high-speed rail and air transport based on the two-stage game theory. Firstly, it builds a one dimensional evolutionary game model from the perspective of passengers to calculate the best competition range. Then, it builds a competition and cooperation relationship model between high-speed rail and air transport from the perspective of price based on Cournot game theory. Finally, it uses the Bertrand game theory to apply the model through a distance perspective, and discusses the competition and cooperation between high-speed rail and air transport in order to find a scientific strategy to achieve a win-win situation. The results show that a distance range of 650 km~850 km is the most intense competition area between air transport and high-speed rail. With the increase of transportation distance, the game strategy of air transport changes from cooperation to competition. On the contrary, the strategy of high-speed rail changes from competition to cooperation.

In this paper, we assumed that machines have different energy consumptions or maintenance costs in the context of green manufacturing, and tried to solve the parallel machine scheduling problem under the condition of cost constraints. To minimize the maximum lateness, an integer programming model MIP was established and an improved algorithm for EDD (earliest due date firstly)-MEDD was designed. Then the feasibility of the MEDD algorithm was proved under the condition of cost constraints, and the worst error bound of the algorithm was also analyzed theoretically. By giving an example, we proved the feasibility of the algorithm. And its performance was verified by a large number of random data experiments. For a small scale, the solution of MEDD was compared with the exact solution of MIP. While the exact solution of MIP is too hard to obtain when it comes to a large scale, the optimal value of MLP of the linear programming relaxation model corresponding to MIP was taken as the lower bound to measure the solution of MEDD algorithm. All these results showed a great effectiveness of MEDD algorithm.

This work studies MapReduce model-based parallel machine scheduling. Each job with arbitrary release time and setup time consists of one map task and one reduce task. The map task can be split and processed on several machines simultaneously, while the reduce task has to be processed on a single machine and it cannot be started unless the map task has been completed, and the processing for any task cannot be interrupted. In this paper, we consider the MapReduce scheduling on parallel identical machines, aiming at minimizing the makespan. We formulate the problem as a mixed integer linear programming model, and develop an improved sine cosine algorithm (ISCA) using differential perturbation and dimension-by-dimension Levy perturbation to obtain a near-optimal solution. Computational comparisons between ISCA and genetic algorithm together with the classical SCA algorithm show that the proposed ISCA algorithm outperforms the other two algorithms. Besides, the ISCA is of an average relative deviation of 3.02% from the lower bound of the problem. Numerical computation verifies the effectiveness of the proposed algorithm.

The characteristics of multi-skilled resources and time window constraints on them are the key factors often considered in the field of software development, engineering design, equipment maintenance and so on. In many real projects, the execution of tasks allows to be interrupted. In this paper, an integer programming model is established for this preemptive project scheduling problem with time-window constraints on multi-skilled resources, and a branch and bound method is developed to construct a search tree to find solutions of the problem where each node represents a combination of tasks. To reduce the number of branch nodes, two valid pruning rules are proposed and the node priority rules are designed. For the task combination of each node, a greedy algorithm is employed to verify resource constraints. Using improved PSPLIB in experiments, the results show the effectiveness of dominance strategies, and the comparisons with the CPLEX and the basic heuristic algorithm reveal the efficiency and effectiveness of the proposed method in solving such problem. The solutions can provide support for the actual project scheduling to make better decisions.

Some efficiency antinomies can be found by example analysis when most of important DEA models are used. Namely, the higher the evaluation standards is, the larger the efficiency value of a fixed decision-making unit. In order to explore the occurrence causes and solution method of DEA efficiency antinomy, this paper firstly proves that the efficiency antinomy exists when some most important DEA models (including CCR model, BCC model, FG model and ST model) are used by examples. Then, it is explained theoretically that the origin of the DEA efficiency paradox lies in the short-tail phenomenon of data in decision making units, and the method for judging whether there is the short tail phenomenon is provided. At the same time, a revised DEA model is given, which can not only overcome the emergence of DEA efficiency paradox, but also improve the accuracy of efficiency measurement. Finally, a comparative study of the related models is given by using the provincial economic data in China from 2000 to 2014.

With respect to the emergency response problem with uncertain scenario predictions, a beforehand-ongoing two-stage decision making method is proposed considering that the prevention actions adopted beforehand will affect the effects of response actions when the emergency is ongoing. In the method, by calculating the utility of each response action, the most desirable response action concerning each prevention action and each scenario is determined. Then, based on the idea of regret theory, the excessive response matrix and insufficient response matrix for pairwise comparisons of prevention actions are constructed, and then an overall anticipated regret matrix is built for selection the desirable prevention action. Further, the global delight value, global regret value and ranking value of each prevention action is calculated according to the overall anticipated regret matrix. Moreover, the ranking of the prevention actions can be determined, and the desirable prevention action and the response action corresponding to each emergency scenario can be obtained. Finally, a case study is given to illustrate the use of the proposed method.

The idempotent, linear and affine properties of initial sequence operator, zero-starting sequence operators and initial zero-starting sequence operator were systematically studied. The closeness axiom of the grey relational degree was defined mathematically. Mathematical definition and physical significance of positive definiteness, affinity and affine transformation isotonicity were also expounded. Generalized grey relational analysis models and their corresponding improvements were essentially constructed based on the areas between sequence interpolation curves. By introducing distinguishing coefficient, the unified representations of generalized relational analysis models and improved models were given respectively. Furthermore, the parallelism, uniformity, affinity, parallel transformation isotonicity, multiple transformation isotonicity and affine transformation isotonicity properties, as well as the applicability were subsequently researched.

Based on the systematic analysis of the factors which influence the warranty strategy and the business performance, a new regional warranty differential pricing strategy on the basis of operational reliability was proposed. A mathematical model reflecting the quantitative relationship between operational reliability and different geographical regions was established in this study. And then a novel three-dimensional differential pricing system dynamics model that considers the regional differences of operational reliability, inherent reliability growth and warranty period was developed. Finally, the simulation analysis for warranty strategy of an air-conditioning enterprise is presented to verify the applicability and validity of the proposed model. The results show that, it would likely contribute to brand influence increase when the warranty period is extended appropriately to a certain threshold. Moreover, a moderate decline in the price of products with higher operational reliability and increase the price of products with lower operational reliability are effective ways to increase profits.

A joint optimization model of economic production quantity and condition-based maintenance policy is proposed in this paper, considering the situation that the production plan and maintenance schedule share the same machine. Using the random coefficient growth model to describe the degenerated condition, the condition monitoring is carried out when a lot is finished. The observed condition composed of two parts, the actual deterioration condition and the random error, once the condition information observed is equal to or higher than the preventive maintenance level, or the actual condition is equal to the failure level, the machine should be renewed. The cost and the length model in the renewal cycle are proposed, then the expected cost per unit time is modeled based on the renewal reward theory. The optimal condition of preventive maintenance level and production time of one lot can be calculated by minimizing the expected cost per unit time. Numerical examples are presented based on the data collected from a steel mill, the results are consistent with the actual situation.

The interaction of public opinion exists in both the real space and the virtual space. To specifically study the evolution process of public opinion in the two spaces, we first analyzed the characteristics of the evolution of public opinion in different spaces and the link between them in the process of evolution. Then, combined with the improved Hegselmann-Krause (HK) model, the online and offline public opinion evolution model based on the supernetwork was constructed. We also proposed a simulation system framework including initialization module, information propagation and interaction module and synchronization module. According to the direction of synchronization, two kinds of synchronization rate, real space-virtual space and virtual space-real space were proposed. Finally, through simulation experiments, the influence of synchronization ratio and space velocity radio on the evolution of public opinion was discussed.

The generally slow growth rates in the aftermath of the global financial crisis have prompted many nations to pursue the political and economic policies that lead the wave of "anti-globalization". To reflect on the phenomenon of "anti-globalization", we need to have a better understanding of the benefits of globalization and its "hidden" costs. In view that there is no literature to explore the impact of export expansion on health theoretically, this paper made the first attempt to examine the relationship between export expansion and health based on China's powerful context. We consider a framework where workers bargain with their employer, and the firm chooses the optimal capital, labor, and materials based on the maximization of profit function. Each worker chooses the optimal effort level by equalizing the marginal benefit of effort, determined through bargaining, with the marginal cost of effort. Based on an extended Grossman health demand model, we systematically examine the channels through which export expansion affects health, i.e., work intensity, wage rate, income inequality, the provision level of public service, and environmental quality. Finally, we give the corresponding policy implications based on our conclusion.

With the transformation of the main contradiction in our society, how to explain the dynamic growth of economic activity in spatial dimension and time dimension has become an important theoretical issue. Based on the theory of integration on spatial agglomeration and endogenous growth, this article bring in the mechanism of endogenous dynamic of transport costs affect heterogeneous enterprise migration, and establish a agglomeration and growth integration model for the analysis of regional traffic policies affecting enterprise spatial location selection and regional balanced development. The study found that:① Better transport conditions between two areas will raise the threshold for the heterogeneous enterprise migration, reduce the enterprise share of the core areas, and will be good for economic growth of the backward areas and reduce the regional economic gap. ② Better transport conditions in core areas will reduce the threshold for the heterogeneous enterprise migration, increase the enterprise share of the core areas and the rate of the economic growth of both two areas, but expand the two regional economic gap at the same time. ③ Better transport conditions in backward areas will also reduce the threshold for the heterogeneous enterprise migration, increase the enterprise share of the core areas, but will be good for economic growth of the backward areas and reduce the regional economic gap within a certain range. ④ Increasing the strength of transport conditions in backward areas will reduce the threshold for the heterogeneous enterprise migration, increase the enterprise share of the core areas, and will be good for economic growth of the backward areas and reduce the regional economic gap. The results can provide a theoretical reference for the scientific formulation of regional transport policy.

In order to verify the feasibility of China's total poverty alleviation in 2020. Firstly, this paper establishes a theoretical model of poverty alleviation and analyzes the exogenous influence in the model. Then, the GM(1,1) is improved according to the rule of poverty alleviation, and a prediction model for poverty alleviation is constructed. And then, the macro data from 2012 to 2016 are used to analyze the progress of poverty alleviation, the results showed that:1) Regardless of the poverty areas or the whole country as the research object, the goal of poverty alleviation by 2020 cannot be achieved under the intensity of poverty alleviation in 2016; 2) When the national poverty alleviation input increases to 1.4656~1.6840 times in 2016, the goal of total poverty alleviation by 2020 will be achieved; 3) Hebei, Hainan, Yunnan and Xinjiang mainly focus on policy-oriented poverty alleviation at present, and these areas have an obvious trend of returning to poverty outside the policy support.

Local volatility model is widely used in the fields of risk management, options pricing, etc. The model can not only describe the "smile" and the term structure of volatility, but can also ensure the completeness of the market. The core goal of local volatility research is to calculate the implied volatility. In this paper, the implied volatility surfaces are built with both parametric and non-parametric methods to obtain smoother volatility surfaces. Parametric method can ensure the absence of arbitrage. Meanwhile, a closed form of solving the local volatility model with non-parametric method is proposed, which can eliminate the approximation error. In addition, the pricing of Shanghai 50ETF option in China based on the local volatility model is studied by comparing effects of the models from aspects of in-the-sample, out-of-the sample and hedging pricing errors. The empirical results show that the non-parametric method is better than the parametric method for errors in-the-sample; the parametric method has better results for out-of-sample and hedging effects. Particularly, both the options pricing and hedging effects of the implied volatility modeling methods are better than un-modeled method in the aspects that the pricing errors can be decreased by more than half and the mean square error can be reduced by 1~2 orders of magnitude.

The existing academic studies always ignored the impact of premature loan default on loan default loss. The main purpose and contribution of this paper is to introduce premature default into the loan insurance pricing model, which corrects the loan insurance pricing error of only considering mature default. Based on the theory of option pricing, this paper obtains the numerical solution of the loan insurance premium of premature default through Monte Carlo simulation. The case studies and empirical results show three findings. First, when the default risk is relatively high, the loan insurance pricing model of premature default can correct the overestimate issue of the loan insurance pricing model of mature default. Second, the relationship between the loan insurance premiums of premature default and corporate default points is non-linear and inverted U-shaped. Third, the time interval of Monte Carlo simulation will affect the loan insurance pricing level of premature default, which implies the impact of information asymmetry on loan insurance pricing.

Based on the economic reality of China, relaxing the implicit hypothesis of firm homogeneity (state-owned and private enterprises) and "perfect bank", the state-owned and private "duality" credit mismatch and the vulnerability of commercial banks were introduced into the DNK-DSGE model with financial accelerator effect. The simulation results show that there are significant differences in the significance of the financial accelerator effect with different financial market constraints. Due to the relaxation of the "perfect bank" hypothesis, the financial accelerator effect is more significant by the double expansion (contraction) mechanism of the external shock through the balance sheet of the enterprise and the balance sheet of the bank. Moreover, due to the existence of the "duality" credit mismatch between the typical state-owned enterprises and private enterprises in China, the elasticity of leverage of the overall external financing risk premium in China is underestimated. It has a certain offset effect on the financial accelerator effect. The simulation results also show that there is a difference in the impact degree of external shocks that are superimposed on credit mismatch and the characteristics of commercial banks' vulnerability. Its monetary policy has the best effect on regulating inflation, and it has a poor effect on regulating total output. At the same time, its external impact is transitive and continuous, and this continuity will be extended for 1~2 quarters. This study can provide a theoretical basis for macro-control decisions.

In view of the ride service market in which online car-hailing service and taxi service coexist, this paper studies the price regulation strategy to ensure the coexistence of the online car-hailing service and the taxi service, considering high-end or low-end online car-hailing service based on different perceived service experience of the online car-hailing service. The regulation targets are Participation (Target 1) and Fairness (Target 2), respectively. This paper compares the price regulation mechanism with these two targets. The results show that when the platform provides the high-end service, and taxi service price is at a high level or a low level, it needs to increase the price of online car-hailing service; otherwise, the target 1 can be achieved without regulation. However, it needs to raise the price of online car-hailing service to realize target 2 under the condition of a lower taxi price. When the platform provides the low-end service, the optimal price of the online car-hailing service is related to the perceived service level of the two services and the taxi service price. Regardless of the high-end or low-end service provided by the platform, the regulation intensity of regulation target 1 is higher than that of regulation target 2.

In the process of enterprise organization and management, effective incentive is one of the most important behavioral driving forces to increase employees' efforts. When the salary and promotion plan of an enterprise are determined, it is of great significance to study how to further improve the incentive mechanism with the help of information theory. In this paper, we study information disclosure policies in all-pay auctions with incomplete information to characterize employees' equilibrium behaviors and the effects of different information disclosure policies on employees' efforts. We obtain that enterprises should choose not to publicly disclose the performance appraisal results in order to fully mobilize employees to work hard, and employees also don't have motivation to tell each other about themselves appraisal results, it ensures the effectiveness of the information disclosure mechanism. According to the conclusion of this paper, we believe that on the basis of the existing incentive theory, we should further optimize the effective incentive to employees and improve the efficiency and competitiveness of enterprises from the perspective of information disclosure mechanism design.

There exists the double moral hazard problem between the start-up and venture capital. Considering the spillover effect, this paper uses the framework of convertible preferred stock to study the influence of government subsidy on micro-motivation of both parties, and further compares social welfare among different support policies from the industrial perspective. Our study found that both ex post subsidy and public service policy can achieve effective motivation and make both venture capital and start-up take socially optimal efforts. Government's investment guarantee policy may lead to welfare improvement under some circumstances, but generally it can not solve the problem of insufficient incentive and even causes misaligned motivation for both parties. From the perspective of the whole industry, public service policy is superior to ex post subsidy in social improvement because of its lower cost, and there still is high uncertainty for government's investment guarantee policy.

This paper focuses on the crowdsourcing system consisting of platform and participants, and constructs a model about supervising behavior of the platform and default behavior of the participants in crowdsourcing process based on differential game theory. We explore the different game strategies under independent decision-making, Stackelberg game with platform and the cooperative decision-making situations. The findings are the return of platform and participants as well as the overall return of crowdsourcing system increases from independent decision making to the Stackelberg game with platform incentive, and then to the cooperative decision-making situations. The crowdsourcing platform can reduce the participants' default risk by the incentive mechanism and affect the return rate of both parties by the regulatory mechanism, so as to select the optimal strategic behavior reasonably and achieve the Pareto improvement. In addition, we set the model parameter based on Zhubajie crowdsourcing platform as case, and do a numerical analysis to validate the theoretical model.

This paper presents a new making-or-outsourcing game model, which is different from traditional logistics capacity planning systems in that it considers cancellation rate of e-commerce order within the allowed cooling-off period. The three-layer dynamic game theory based cooperation of gradient includes completely cooperative game policy, non-cooperative game policy, and incompletely non-cooperative game policy, and then the first two cases has been divided into three-stage dynamic game process. The equilibrium solution of each sub-game in the first two cases and the optimal solution set of homemade-or-outsourcing logistic service capacity problem are obtained by the backward recursive algorithm. Further, in the third case three kinds of sub-game coordination mechanism—cost sharing, profit distribution and risk aversion—have been designed to enhance the flexibility of the model. Numerical examples and analyzes show that the decision maker can effectively achieve the Pareto optimization of dynamic game under the influence of withdrawal behavior and cost change.

This paper established secondary distribution model of optimization problem, aiming at the minimum logistics cost under optimal layout of the workshop, and ant colony-genetic hybrid algorithm is used to solve quadratic assignment model. The hybrid algorithm combined the advantages of the ant colony algorithm with the genetic algorithm, using the solution of ant colony system as the initial population of the genetic algorithm, overcoming the flaws of converging slowly, falling into the local optimum of the ant colony algorithm and easy to premature convergence of the genetic algorithm, which will achieve the global optimal model. This paper regarded a machine factory workshop as an example, using MATLAB to solve the results, which shows that:it will save 10.6% logistics fees by using the new layout of genetic ant algorithm than the original program, while it is better and faster to use the hybrid algorithm to solve the shop layout optimization problem than the ant colony algorithm or genetic algorithm.

This paper investigates international migration for top talent with three kinds of analysis tools—bibliometrics, complex network theory and system identification. First, according to bibliometerics, the clear definition of top talents is given, and the method of collection of historical data about the amounts of top talents of each countries is introduced. Moreover, the framework of international migration is studied from algebraic graph theory, matrix theory and complex network theory. And the relationship between complex network and international migration is discussed. Also, the known and unknown parameters of the proposed framework are distinguished. Based on the model, the overall situation of international migration of top talents can be represented quantitatively. In addition, we collect the residing information of top talents, and establish the corresponding database. Furthermore, by employing the least squares method, this paper proposes two approaches to identify the unknown parameters, and the obtained identification results are testified based on statistics theory. Finally, the migration of top talents between some major and typical countries is discussed according to proposed method, and the analytic results and the effectiveness are testified.

The real-time pricing mechanism is an ideal method of the smart grid in the future. Based on the social welfare maximization model, the real-time pricing strategy of smart grid is studied in this paper. According to the working characteristics of appliances, appliances are divided into three categories, which are must-run appliances, elastic appliances and semi-elastic appliances. For the coupling property about time of power consumption of elastic and semi-elastic appliance, a multi-time slots model is established. The multi-time slots model is decomposed into a set of single-time slot optimization problems by the relaxation method. Based on the theory of duality, a distributed algorithm is proposed. The real-time electricity price is obtained. In this algorithm, users do not need to disclose their specific power consumption information to the energy suppliers and other users, which protects users' personal privacy. Numerical simulation verifies the rationality of the model and the effectiveness of the algorithm.

This paper mainly studied the morbidity problem of six different derived models of GM(1,1). Firstly, we discussed the morbidity of identification parameter coefficient matrix by using the condition number of parameter estimation matrix B^TB and eigenvalue analytical theorem. According to the degree of morbidity, the derived models were classified. Furthermore, the reasons for the morbidity of various models are analyzed, and then the vector transformation method was used to improve the morbidity models. On the basis of this, the differences between the defined model and the derived models are compared on the modeling mechanism and the calculated amount. The results show that:1) The derived model of b and connotative derived model belong to the first category, i.e., they are non-morbidity. The defined model, the derived model of x⁽¹⁾ and the discrete model belong to the second category, i.e., they have general morbidity. The exponential derived model and the derived model of x⁽⁰⁾ belong to the third category, i.e., they have very serious morbidity. 2) Compare with the derived models, the defined model has obvious advantages on the aspects of modeling mechanism and calculated amount. Finally, several numerical examples were used to verify the rationality of the classification and analysis results.

A key problem in prediction theory is to improve adaptiveness to data characteristics. This paper proposed a novel method called buffered adaptive grey rolling model or BARGM model, which combines the buffer operator and grey rolling model. First, the new model decomposes original sequence into continuous data slices, and uses feedback input to adjust modeling data by buffer operator with variable weight on each data slice, then a extended grey forecasting model is utilized to model the adjusted data slices stepwisely and generate the extrapolation values. With comparison to GM(1,1), BARGM has two obvious features:Changing the monotonicity of traditional time response function and strong expansibility. The case study uses the BARGM and benchmark models to analyze China's greenhouse gas emission data, and the results demonstrate that the accuracy of fitting and prediction improve obviously, and prove the new model's effectiveness.

Before a social security event occurs, it usually goes through a process of planning and preparation. The social security event that is brewing might be identified in advance according to the behavior and actions of the participants in the preparation process. Although the preparation actions hardly show abnormal characteristics separately, an underlying event might be found if multiple participants' actions and their relationships are comprehensively analyzed. The paper assumes that some of the actions of participants in the preparation process of some social security events can be observed. A social security event recognition method based on plan recognition is proposed. The social security event recognition model framework is constructed firstly. The domain knowledge and problem model of social security event recognition are described. Then the corresponding event recognition algorithm is proposed employing the method of plan recognition as planning (PRAP). The algorithm is capable of reasoning using domain knowledge, and identifying the possible event dynamically. Finally, an experimental example is designed based on the personnel gathering event, and the effectiveness of the method is tested. The experimental results show that the method can accurately identify the social security event corresponding to the participants' actions, and has strong ability to identify in advance. It can improve the monitoring and early warning capability of social security events.

In recent years, power grid systems are more and more expected to be a good performance in facing emergencies, and using the concept of resilience to construct power grid system can avoid losses in the whole emergency period. In this article, the characteristics of resilience are depicted in stages with the theory of emergency management, and a quantitative method for the assessment of system resilience is proposed. The method focuses on the ability of the system to maintain stability, resisting interruptions, and restore performance, based on the characteristic of power network which includes operation mode, component physical strength and network topological structure. The resilience evaluation metric is used to describe the measures which can enhance the resilience of power grid. Finally, the simulation is carried out by using PSCAD software, the N-1 criterion is selected as an example to prove the rationality of resilience metric. Meanwhile, the N-1 criterion has also been confirmed to enhance the resilience of the power grid system. This is illustrated using the IEEE14-bus test system.

The vehicle routing problem with simultaneous stochastic pickup and deterministic delivery (VRPSSPDD) is the further study of vehicle routing problem with simultaneous pickup and delivery (VRPSPD). The problem is more complicated than VRPSPD due to the uncertainty of customer's pickup demand. Based on the pre-optimization and re-optimization strategies, a two-stage model of VRPSSPDD was proposed. In pre-optimization stage, pre-optimization scheme was generated by transforming the stochastic constrain of customer's pickup demand to a certain constrain and checking vehicle capacity constraints. In re-optimization stage, a new re-optimization strategy was used to deal with the so-called failure point in pre-optimization scheme. According to the characteristics of the problem, the hybrid genetic algorithm with variable neighborhood descent was proposed which combined genetic algorithm with the advantages of local search ability of the variable neighborhood descent. In this metaheuristic, the separation of distribution network information was used to encode, and then strategies combined the adaptive population range searching and adaptive number of iterations were used to balance the diversification and exploitation in the algorithm iteration process. Numerical results show that the model and metaheuristic we proposed are rather effective.