Barrier option is a popular over-the-counter derivative in the Chinese market. Due to the discontinuity of its returns, financial institutions are mainly faced with the problem of delta value fluctuations in the process of dynamic hedging, resulting in higher hedging risks. We propose an efficient and stable willow tree method for barrier option pricing and greeks calculation for dynamic hedging of barrier options assuming the underlying asset price follows Merton's jump-diffusion model, which can also be extended to other stochastic processes. Compared with the existing methods, the willow tree method is more stable in calculating the delta, and the hedging cost is lower. An empirical analysis of the hedging effect of barrier options on the Shanghai Stock Exchange 50 Index is conducted from January 1, 2010 to September 30, 2021, and the model parameters are calibrated from the market data. The numerical results show that the willow tree method reduces hedging costs and hedging risks, and it can provide a new approach for domestic financial institutions to hedge barrier options and related structured products.

Classical Mechanics Principle of Control Engineering (System) depends on that 3 state variables including position, velocity and acceleration can be accurately constructed and estimated for the controlled system output, and the 3 state variables are used to make negative feedback control functions for the control system based on Newton's Laws of Motion. In the reference paper (Kai P A and Shen Z L, 2022), an OUAM observer (Observer based on Uniform Acceleration Movement) is constructed by Kalman filter and an MFCNLM system (Model-Free Control based on Newton's Laws of Motion) is designed based on Newton's Laws of Motion. The desired transient process output of the closed loop system is designed with the desired transient process time T. All parameters in the control system are only calculated based on the desired transient process time T of system output without controlled plan model. From the reference paper (Kai P A and Shen Z L, 2022), the theory and application of Newton's Laws of Motion in the MFCNLM system and PIDCC system (PID Control with Compensator) are emphatically analyzed in the paper. The unbiased estimation of OUAM observer and the effectiveness of MFCNLM system are demonstrated. The unity of classical mechanics principle are explained in these control systems. A simple and effective method is designed for time-varying system with time-delay (dead-time) loop in the MFCNLM system and PIDCC system, 2 simulation examples in MFCNLM and PIDCC systems demonstrated fine control quality and robust performance of the design method in the paper.

To handle the tracking control problem of unknown strict feedback nonlinear control systems with dead zone input, a projection-based adaptive command filtered and finite-time control strategy is proposed based on immune function. The immune function and the extended state observer are utilized to estimate the unknown information of control systems with dead-zone input. The command filtering is used to cope with the derivative explosion problem occurred in the backstepping method and the error compensation mechanism is established to diminish the impact of the filtering error on tracking accuracy. The projection operator ensures the boundedness of adaptive parameters. Compared with the literature on adaptive backstepping constrained control based on a barrier Lyapunov function, this paper simultaneously guarantees system states, the compensated tracking errors and adaptive parameters within pre-assigned certain bounds and ensures the boundedness of all closed-loop system signals. It enhances the controller’s convergence rate by using the finite-time control. Finally, a simulation example shows the effectiveness of the proposed control strategy.

The large-scale interaction data of the online live streaming platform provides experimental datasets for the quantitative analysis of human behavior, and offers a new opportunity for the mining of the online interaction mechanism with collective dynamics. Given the lack of empirical research on real-time collective interaction, this paper collects a one-year-long comprehensive dataset of real-time live streaming statistics, involving more than 1.9 million streamers from Douyu (the largest live streaming platform in China), and designs a generalized evolution model for exploring the interaction mechanism between streamers and viewers. First, we construct a viewer-streamer bipartite interaction network representing the dynamics of the entities in the platform, and then propose an evolution model with adjustable preference strength of viewer-streamer interaction. The preference strength can be adjusted with two parameters:The fraction of random choice and the preference coefficient of viewers. Experiments on empirical datasets show that the model can accurately and robustly predict the evolution process when all viewers have linear preference on the number of existing viewers attracted by the streamer when they select a streamer to interact with. This paper reveals the dominating mechanism of preferential attachment for the viewers selecting a streamer and reflects the human tendency and preference for valuable content, confirming the cumulative effect of reputation or word-of-mouth in social systems. Our study provides a quantitative model for exploring the interactive behavior characteristics and internal mechanism of large-scale online crowds in live streaming, and is of great significance for describing and predicting the formation and development of social relationships in more general settings.

Model uncertainty usually exists in the prediction for longitudinal data. To solve model uncertainty, we propose an optimal model averaging prediction method based on semi-parametric mixed effect models. The optimal weight vector is obtained by minimizing a leave-subject-out cross-validation. This paper shows that when all candidate models are misspecified, our proposed method is asymptotically optimal in the sense that it yields a squared prediction loss that is asymptotically identical to that resulting from the infeasible best-possible averaging estimator. In a different scenario, we show that our method can put the weight one to the correctly specified models. Both simulation study and empirical example show the superiority of our proposed estimator over other competitive methods.

As looking for high-quality online public opinions from mass reticula data is the practice of the new concept of online public opinion, both quantity and quality aspects should be considered by relevant studies. Based on the three-dimensional evaluation system of the quality of online public opinion, through the change and reconstruction of the nodes and edges of the public opinion supernetwork model, an Opinion-Noise Detection Supernetwork model was proposed, in which there are four subnetworks:Environmental subnetwork, emotional subnetwork, social subnetwork and content subnetwork. The noumenon of online public opinion “noise” refers to the public opinion data that cannot provide suggestions for the formulation of management decisions. Based on the proposed model, 18 characteristic indexes were extracted. Finally, by employing machine learning algorithms, the public opinions with high quality were successfully identified.

Improving green total factor productivity (GTFP) is the core of establishing a green logistics system. This paper constructs a global SBM model of undesirable output, and employs the GML index to calculate the GTFP of the logistics industry in 30 provinces selected from China between 1998 and 2020. Then, the Dagum Gini coefficient is used for analyzing regional differences and the causes. Finally, a spatial econometric model is established to identify the convergence mechanism. According to the research findings: During the sample period, while the GTFP of logistics in China gyrates up, growth imbalance remains a concern, with the GTFP level in the east being far higher than in the west; The differences between regions are the primary cause of the imbalance; the difference in the rate of contribution in the same region stays at around 30%; the regions with lower GTFP levels in logistics are expected to catch up with those with higher GTFP levels and finally achieve the same level; the growth and convergence of GTFP in logistics are affected by spatial factors and show regional heterogeneity; the eastern region may optimize the industrial structure, while the middle and western regions may increase their investment on energy infrastructure and R&D to bridge the growth gap of green logistics in the region; coordinated development of different regions can be realized based on a comprehensive measurement of the positive impacts of factor inputs on the local region and negative impacts on neighboring regions. The aforementioned analysis provides a theoretical basis for the construction of the green logistics system that will help promote the healthy and sustainable development of the logistics industry in China.

In the propositional logic system $\mathscr{L}^{*}_{n}$, the concepts of $p$-randomized truth degree, $p$-randomized similarity degree and $p$-randomized pseudo-distance are proposed. $p$-randomized logical metric space ($F(S), \rho_{p}$) is established, and the concept of $p$-randomized divergence degree is proposed in the $p$-randomized logical metric space ($F(S), \rho_{p}$). It is pointed out that the $p$-randomized divergence degree of the theory and the values of randomized $n$-point distribution are closely related. It is proven that the $p$-randomized divergence degree of the set of atomic formulas with different values of $n$-point distribution sequence can be full of the real number interval (0,1].

This paper investigates the effect of individual investor attention on the herding effect of China's stock market. Using Baidu Index as a proxy of individual investor attention and constructing an indicator to measure the strength of individual investors' herding effect, this paper conducts an empirical study on the performance of China's A-share market from 2017 to 2021. The empirical results show that:1) Individual investor attention has a significant positive impact on the herd effect in the stock market; 2) individual investor attention will have a more significant positive impact on the herd effect in the stock market when the stock reaches the limit up or down; 3) small-cap companies individual investor attention has a more significant impact on the herd effect. The robustness test results show that the conclusions are robust.

This paper presents a noncooperative-cooperative biform game framework to analyze how different power structures (the simultaneous model, the manufacturerleader model, and the retailer-leader model) to affect the product pricing and lowcarbon technology investment decisions in a low-carbon supply chain consisting of a manufacturer and a retailer. The results show that: 1) There is the unique lowcarbon technology level and cost-sharing ratio, that make the retailer and supplier maximize their profits in the three decision-making models under some conditions; 2) The supplier’s low-carbon technology level has greater development potential in the retailer-leader model; 3) There is an inverted U-shaped relationship between the low-carbon technology investments cost-sharing ratio and consumers’ low-carbon preference; 4) From the perspective of the supply chain system, the different development periods of low-carbon supply chain need different market structures, rather than fixed in a specific market structure. This study contributes theoretical methods for lowcarbon supply chain production and operation, and also provides new solutions for achieving carbon peak, carbon neutral, and double carbon goals.

The structure description and index evaluation of consecutive-k-out-of-n type redundant systems is a key and difficult issue in the field of reliability. In this paper, we establish a model of two linear m-consecutive-k-out-of-n: F systems with sparse d that sharing components. Based on the finite Markov chain imbedding approach, an evaluation method for the joint reliability function and the joint signature is proposed. In addition, we study the reliability evaluation and the structure comparison of smart street light systems based on the model of m-consecutive-k-out-of-n: F systems with sparse d that sharing components, which not only verifies the correctness of the finite Markov chain imbedding approach by the traditional definition method, but also shows that it can be applied to the evaluation of the joint reliability and the joint signature for large smart street light systems. Therefore, the model and the method studied in this paper can provide the basis of reliability evaluation and management decision for redundant systems with shared components in engineering application.

This paper is concerned with an optimal contraception control problem for a size-structured vermin population. The state system model consists of a first-order partial differential equation with a global feedback boundary condition and two ordinary differential equations, and the control function is taken to be throwing amount of contraception medicaments. Firstly, the existence of a unique non-negative bounded solution to the state system is established, and the continuous dependence of solutions on the control variable is shown. Then, the Euler-Lagrange equations describing the exact structure of the optimal strategies are derived by constructing a proper adjoint system and relative normal cone. Finally, the existence of a unique optimal policy is proved via Ekeland's variational principle and fixed-point method. This work supplies a novel modelling approach for contraception control of vermin.

As an important open source software in the field of statistics, R language has a long history of development and a relatively mature ecosystem. This paper explores the core components and dependencies of R language packages from the perspective of complex directed networks, divides the dependency networks between packages, and conducts an in-depth study of their developmental lineage, so that R language developers and users can quickly understand R language. Our study shows that the dependency relationships among the R packages obey the power-law distribution and “small-world” phenomenon; the dependency network of R packages includes five subcommunities “Statistical Modeling”, “High-Performance Computing”, “Data Visualization”, “Statistical Modeling”, “Data Visualization”, “Web technologies”, “Bioinformatics”. In summary, this paper has found the following:The R language ecosystem meets the needs of the entire data analysis process, scales with the times, attracts developers from all over the world, and focuses on the long-term maintenance of the package's health. Finally, the paper explores the open source model of R language to explore the implications for domestic open source software and its ecosystem.

Aiming at the inventory routing optimization problem of refined oil secondary distribution under random demand, considering the storage capacity of each petrol station, the constraints of loading and unloading with full compartment, and one-to-many services in the process of refined oil secondary distribution, by setting the replenishment quantity of each petrol station as an integer multiple of the single compartment capacity, a two-stage stochastic integer programming model is formulated to minimize the sum of distribution cost and expected loss. A multi-cut L-shaped algorithm is developed. Based on the multi-cut L-shaped algorithm, a two-phase algorithm is designed for solving large scale instances, two improved strategies are embedded in the approach to accelerate the convergence speed. Different scale instances are used for simulation, the effectiveness of the improved multi-cut L-shaped algorithm and the fast effectiveness of the two-phase algorithm are verified respectively. Compared with other methods, when solving the large scale instances, the average solving time of two-phase algorithm is reduced by 31.34% and Gap of the average cost is lower than 2.63%. The research results provide theoretical basis and algorithm support for making the secondary distribution plan of refined oil.

In the decision-making process, how to obtain optimal group decision scheme under the premise of achieving the expected utility of individual decision-makers, is one of the main contents of multi-criteria group decision making(MCGDM). However, existing methods of MCGDM didn't consider decision-makers' expectations and risk preference for individual attributes. In this paper, we study the problem of MCGDM considering decision-makers' aspiration satisfaction. Firstly, we discuss how to apply the best-worst method to MCGDM to determine the weight of attributes. Additionally, we rank the score of alternatives by considering the aspiration and risk preference. Finally, we present a new methodology by a combination of best-worst method(BWM) and aspiration satisfaction function to solve the problem of MCGDM. We verify the feasibility of the proposed method through an example. Furthermore, we do a simulation analysis for two attributes with the largest weight.

This paper considers an MAP/PH/1 queueing system with impatient customers. Customers arrive at the queueing system according to a Markovian arrival process, each of the customers requiring a service that is of phase type, and the impatient time of customers is assumed to be exponentially distributed. For analyzing the queueing system, a level dependent quasi-birth-and-death process is constructed. Firstly, the stability condition of the system is obtained by using the mean drift technique. Then the stationary probability vector of the quasi-birth-and-death process is given by using the RG-factorization of Markov process. Based on the stationary probability vector, the probability distribution of the stationary queue length and the average stationary queue length are obtained. Moreover, a Markov process with an absorption state is built for analyzing the sojourn time of any arriving customer in the system, and the probability distribution of the sojourn time and the average sojourn time are given. Finally, the effect of some crucial parameters on the performance measures of the system is analyzed by means of numerical examples.

An optimal control problem and the basic properties for solutions of a population system of hierarchical age-structured are investigated. First, by using the fixed point theorem, the existence and uniqueness and boundness of the nonnegative solution are proved. Then, a feedback optimal control law is established by means of adjoint system and normal cone concept. Last but not least, we obtain the existence of a unique optimal control via Ekeland variational principle and fixed point theorem.

Consider that an online retailer can cooperate with a physical retailer to allow consumers to pick up online orders in the physical store. By developing competitive pricing models in the case without cooperation and with cooperation, we investigate the condition under which two retailers are motivated to cooperate and how the cooperation affects the pricing competition and the express firm's decision of delivery efficiency. Results show that two retailers are motivated to achieve a win-win cooperation although the cooperation intensifies the pricing competition when the proportion of time-sensitive consumer is high. This occurs especially when the product differentiation level is low and the convenience for consumers to pick-up online orders in store is more. Because the online retailer can benefit from the increased market penetration while the physical retailer can benefit from the increased store traffic. These positive benefits will outweigh the negative competition effect. Additionally, the express firm will improve its delivery efficiency to increase the profit when two retailers cooperate for picking up online orders in store.

This paper constructs a logistics service supply chain (LSSC) consisting of two logistics service providers (LSPs) and one logistics service integrator (LSI), considers the emergency decision under the background of both demand disruption and cost disruption, introduces two influencing factors, data empowerment and fairness concern, and then solves and compares the optimal decisions of the LSSC under four different scenarios. The results show that:The pricing of emergency logistics service product, the level of emergency logistics service increase with the disturbance of demand, and decrease with the disturbance of cost. The impact of disturbance of demand on the LSI's utility is related to the unit fee of emergency disposal. The decisions of supply chain members increase with the degree of data empowerment, while the impact of data empowerment on the LSI's utility depends on the investment coefficient of data empowerment. Fairness concern has a positive impact on the pricing of emergency logistics service product, the level of emergency logistics service and LSI's utility. When the data empowerment investment coefficient exceeds a certain threshold, the additive positive impact of data empowerment and fairness concern on LSI's utility is insufficient to cover total data empowerment investment, and this threshold is the "upper limit of effective investment" for the LSI to carry out data empowerment. This paper is helpful to grasp the influencing rules of demand and cost disruption, data empowerment and fairness concern on emergency decisions in LSSC, and provides reference and guidance for strengthing emergency capacity building.

As the error in a regression model obeys an asymmetric distribution, it has been shown that the second-order least squares estimator is more efficient than the ordinary least squares estimator. This paper considers Bayesian Ψ_q-optimal designs for multi-factor nonlinear models under the second-order least squares estimation. For such a multi-factor nonlinear model with a constant term, its Bayesian Ψ_q-optimal design via the second-order least squares estimator is the same as that derived from the ordinary least squares estimator. For the multi-factor nonlinear model without a constant term, if orthogonal assumptions are satisfied for Bayesian Ψ_q-optimal designs on marginal models, then Bayesian Ψ_q-optimal design for multi-factor nonlinear model can be obtained from the product design of Bayesian Ψ_q-optimal designs on marginal models. Several examples are presented to illustrate the effectiveness of theoretical results.

The evacuation of overseas Chinese is an important issue in emergency management. Based on the minimization of evacuation cost and evacuation time, this paper proposes a multi-objective planning nominal model for the evacuation of Chinese nationals. Considering the uncertainty of the cost of evacuation, we adopt the idea of robust optimization and introduce two types of uncertain sets (box and ellipsoid). We then establish robust location routing models and reformulate them into tractable LP and SOCP. Finally, a numerical example is given based on the Libyan evacuation operation in 2011. For different conservative parameters, the Pareto-effective evacuation plan is calculated, which verifies the feasibility and effectiveness of the model.

Complex networks have been widely used to explore the regular pattern of complex systems. This paper uses the quantile graphs method to map the daily closing price series of six stock indexes in different markets to a complex network. It analyzes the characteristics of the quantile graphs of stock indexes, and explores the changes of the network structure of stock markets in two different regions. The results show that, firstly, the network characteristics of stock index series quantile graphs in the same market are similar, but there are great differences between these two markets. Secondly, Shanghai Securities Composite Index and Shenzhen Securities Component Index have long-range correlation, and Hong Kong Hang Seng index is relatively random, but the three stock indexes in the US market, include S&P 500 Index, NASDAQ Composite Index and Dow Jones Industrial Average, are inversely long-range correlation. Finally, the quantile graphs of the two markets have different community structures. This method reveals the nature and potential dynamic behavior of stock markets in different regions from a macro perspective, and it can provide a wealth of information for stock index forecasting.

In this paper, we propose a robust adaptive control method based on singular perturbation theory for a class of non-affine nonlinear systems with parameter uncertainties and unknown disturbance terms. Firstly, a fast dynamic subsystem is constructed for the system through the control input to introduce time-scale separation. Then, the closed-loop system can be decomposed into two order-reduced subsystems:A boundary layer subsystem and a reduced slow subsystem, on the fast and slow time scales, respectively. On the fast time scale, the structure of the boundary layer subsystem is designed to make it exponentially stable around the equilibrium point. On the slow time scale, a robust adaptive controller is designed for the reduced slow subsystem with parameter uncertainties and unknown disturbance. According to singular perturbation theory, the tracking performance of the closed-loop system can be approximated by the reduced slow subsystem. The proposed control method considers the effects of parameter uncertainties and disturbance terms, achieves the control goal without ignoring the non-affine structure, does not rely on the time-scale separation of the original system, and avoids the "complexity explosion problem" in backstepping method. Simulation results with comparisons to reference control methods verify the effectiveness of the proposed control method.

To explore how to effectively control the dissemination of public opinion on social media platforms in view of the hype and manipulation of social media by online promoters. We construct an evolutionary game model based on four parties, including online promoters, social media platforms, government regulators and Internet users, analyze the stabilization strategies of each game player, and explore the influence of key elements on the game model through experimental simulation. The following conclusions were obtained: 1) Timely disinformation by authoritative media can effectively stop the spread of false public opinion information on social media platforms; 2) Strengthening effective supervision by government regulators on network pushers and social media platforms and increasing the punishment for violations can serve as a strong warning to network pushers and urge social media to standardize the process of public opinion information pushing; 3) The public opinion information released by mainstream media platforms is more reliable, and netizens should check the gossips in time. Accordingly, we suggest the government to effectively regulate the dissemination of public opinion on social media platforms, so as to purify the online information space, protect the rights and interests of netizens, and maintain social stability and unity, and provide reference for decision-making.

This paper analyzes the climate change of Hong Kong, China based on the climate data of Hong Kong, China observatory from 1884 to 1939, and from 1947 to 2016, using the Mann-Kendall trend test, the t-test, the wavelet transform, and the cross-wavelet transform. The results of the Mann-Kendall test and the ttest show that during the first period from 1884 to 1939, the growth rates of the annual average minimal and maximal temperatures in Hong Kong, China are equal, while in the second period from 1947 to 2016, the growth rate of the annual average minimal temperatures is significantly higher than that of the annual average maximal temperatures. For doing the temperature mutation test, the missing data of the period from 1940 to 1946 is has been imputed by China, Macao’s data in the same period with appropriate modification. The result shows that the temperature had a significant mean abrupt change in 1958 in Hong Kong, China, and 1997 was a suspected year of abrupt change. The wavelet transform shows that there exist multi-scale periodic changes in temperature and precipitation in Hong Kong, China, where the first major periods of temperature and precipitation were 52a and 42a respectively; the crosswavelet analysis shows that the ENSO characteristic values Nino3.4 and SOI, the correlation with temperature, and precipitation in the whole time is not significant, but there exists a local correlation.

In this paper, a neuroadaptive tracking control algorithm is proposed for a class of uncertain strict feedback nonlinear systems with time-varying asymmetric new state constraints and unknown time-varying control gains. Unlike the commonly studied time-varying state constraints that are only related to the running time, this paper also considers the influence of the desired trajectory and the partial state of the system on the constraint boundary function. This new type of state constraints includes the commonly studied time-varying constraints and constant constraints, so the new state constraints researched here are more general and practical. The derivatives of such constraint boundary functions will involve uncertain nonlinear dynamics, which are no longer suitable for controller design. In this paper, the neural networks and virtual parameter technique are combined to deal with the uncertain nonlinear parts. This method does not need to estimate the weight vector parameters directly, which greatly reduces the computational burden. In addition, the complexity of controller design and stability analysis is reduced by constructing a non-piecewise continuous asymmetric barrier Lyapunov function. The control algorithm proposed in this paper can ensure that the system can achieve better tracking performance without violating the time-varying asymmetric new state constraints, and both theoretical analysis and simulation results verify the effectiveness and superiority of the presented control algorithm.

The problem of attack detection for the physical layer actuator of cyber-physical systems is studied in this paper. First, a dynamic model is established to describe the whole cyber-physicalsystems. On the premise that there is an attack signal in the actuator, a class of attack detector is designed based on the assumptions. The Lyapunov stability theory is applied to analysed the stability of the system, so that the observer satisfies the H_∞ and L₂-L_∞ performance conditions respectively, and finally it can be transformed into the form of linear matrix inequality, in this way, the gain matrix can be solved. Finally, a simulation example is given to demonstrate the accuracy of the design method.

Based on the classical inverse Radon transform, the Second-order Divideddifference Back Projection (SDBP) method for realizing inverse Radon transform is proposed in this paper. For discrete projection data, the discrete projection sampling sequence is transformed into continuous projection function by data interpolation. Through logical derivation, a filter design model based on interpolation kernel functions is proposed by using SDBP formula. As an application of the filter design model, a new kind of filter is obtained by applying triangle function. Compared with traditional filters, the new filter has controllable parameters to adjust the performance. Such that some features can be enhanced on the basis of actual needs, so as to obtain better reconstructed images.

With the rapid increase of transaction volume in the land market and frequent usage of land as financial assets, traditional methodologies for determining land value are gradually unable to meet the needs of the current market due to their high cost and strong subjectivity. Therefore, cheap and efficient intelligent approaches are urgently needed. Based on previous literature, this paper takes land’s basic characteristics, business information nearby, and local macroeconomic information as the main pricing factors, and applies Linear Regression, Decision Tree, Artificial Neural Networks, and Deep Learning model to land evaluation. The data for training and testing the models is composed of 58, 815 parcels of land traded through bidding, auction, and listing, collected from Chinese websites in the period of January 2016 to June 2019. The study demonstrates that among those models, XGBoost outperforms all the other models and is well suited to different types of land. Furthermore, we measure the influence of enriched attributes on model performance and find that all three types of factors are indispensable for determining the price of land, especially the max floor area ratio and cities land prices, which means the macro-market value of the land and the degree of land availability are the most important factors.

Computing the greatest common divisor of polynomials is a fundamental problem in computer algebra and is one of the typical applications of subresultant theory. Euclidean algorithm is a classical method commonly used for computing the gcd of several univariate polynomials, where the phenomenon of coefficient inflation often appears. As a practical solution to this problem, the modular method can effectively control the size of coefficients and is helpful to achieve high computational efficiency. In this paper, a modular method for computing the gcd of several univariate polynomials is proposed. As the most key issue in modular arithmetic, a criteria for selecting good primes is presented by establishing the relationship between the generalized subresultants of a polynomial set and its greatest common divisor under homomorphic mapping. Besides, an upper bound for the coefficients of common factors for several polynomials is derived with the Landau-Mignotte inequality. Compared with the previous approach based on the recursive gcd computation of two polynomials, the new method can compute the gcd of several polynomials with a non-nested loop, which significantly simplifies the computing process and improves the computational efficiency.

Adaptive control charts are a hot research topic in Statistical Process Control, and widely concerned by practitioners. This paper first introduces the idea of the weighted likelihood ratio test into the design of adaptive exponentially weighted moving average (AEWMA) control charts and develops an AEWMA chart for joint monitoring the process mean and variance (denoted by the AWLRT chart). The effect of the smoothing parameter on the proposed AWLRT chart is investigated in terms of the mean and standard deviation of run length. Subsequently, the out-of-control performances of the AWLRT and other existing control charts for monitoring the process mean or (and) variance are compared. The results show that the proposed AWLRT chart has consistently optimal performances. Finally, the application of the proposed AWLRT chart is illustrated by a real example.

The state-owned property of urban land and the rapid progress of urbanization in China make urban housing prices closely related to land finance and become an important factor affecting economic growth. The paper puts urban housing price, land finance and economic growth into the same analytical framework to build a simultaneous equation model. Based on the panel data of 277 cities at and above prefecture level in China from 2011 to 2019, the paper empirically tests the interaction mechanism between urban housing price and land finance and the mechanism affecting economic growth, and analyzes the regional heterogeneity according to the four major regions of the country. The results show that the positive interaction between urban housing price and land finance is significant, and the interaction of the eastern and central areas is significantly weaker than the western and northeast areas. The urban housing price has a significant positive impact on economic growth, which is weaker in the east and west than in the middle. The impact of land finance on economic growth shows obvious regional heterogeneity, with non-significant impact in the middle and northeast, and unlimited impact in the east and west.

This paper considers a double-ended queueing system involving taxis and customers at a taxi-stand under the assumption that there is limited waiting space both for customers and for taxis, and that the taxis serve the customers in bulk. This queueing system can be described by a group of finite partial differential equations with integral boundary conditions. When the service rate is a constant, the expression and properties of the time-dependent solution of the queueing model has been studied. First of all, the expression of the time-dependent solution of the model has been determined by using the method of characteristics, then quasi-compactness of the operator semigroup, which is generated by the underlying operator corresponding to the model, has been proved, thus exponential convergence of the operator semigroup to a project operator has been obtained, and exponential convergence of the time-dependent solution of the model to its steady-state solution has been shown.

The "carbon peaking and neutrality" goal of the Chinese government puts forward new requirements for the coordinated emission reductions in supply chains. This paper considers a low-carbon supply chain consisting of a single supplier and a single capital-constrained manufacturer. The two parties apply a "two-way cost-sharing" mechanism on carbon abatement to make joint emission reduction. Specifically, the capital-constrained manufacturer raises money from a competitively-priced bank to accomplish production, carbon abatement and even insufficient carbon emission permits procurement. On the basis of solving the equilibrium strategies of the participants including the supplier, the manufacturer and the bank, this paper explores the multi-contract coordination of the capital-constrained low-carbon supply chain based on the "two-way cost-sharing" contract. It is found that the combination of the wholesale price, the two-way carbon-abatement cost-sharing and the revenue-sharing contracts can achieve coordination and Pareto improvement of the low-carbon supply chain. When considering the carbon trading market, an additional carbon trading cost-sharing contract needs to be further included for achieving the coordination. The relevant results can provide theoretical guidance for enterprises' integrated decisions on operations, carbon abatement, as well as for joint emission reductions among supply chain members.

This paper considers an M/G/1 queueing system with admission control and overhaul policy, in which at most M(≥ 1) customers are allowed to enter the system during system's overhaul period. Under any initial state, we employ the renewal process theory, total probability decomposition technique and Laplace transform to discuss the transient queue length distribution of the system, and obtain the expressions of the Laplace transform of the transient queue length distribution with respect to time t. Then, the recursive formulas of the steady-state queue-length distribution are obtained by using L'Hospital's rule. Moreover, some special cases such as M→∞ and P{Y=0}=1 are also discussed. At last, applying the renewal reward theory, the explicit expression of the long-run expected cost per unit time is presented, and numerical examples are provided to determine the optimal control policy M^* for economizing the system cost as well as the optimal two-dimensional control policy (T^*, M^*) when the overhaul time is a fixed length T.

Due to natural disasters, public epidemics and other reasons, the risk of failure has become the most important and most concerned type of risk in agricultural product distribution centers. Aiming at the problem of location and route of agricultural product distribution center with failure risk, this paper firstly uses elasticity to measure the ability of the system to cope with failure, and builds a nonlinear mixed integer programming model with total cost and delivery time as the goal. Secondly, a multi-objective hybrid genetic algorithm (IGSSA) based on local search of simulated annealing is proposed for model solving. Finally, IGSSA is compared with three multi-objective algorithms in the generated test cases. The research results show that the proposed model can effectively deal with the failure problem caused by the distribution center. At the same time, IGSSA has better search depth and breadth, which is more effective for optimizing the established model.

In order to study the long-term impact of government subsidies and manufacturers' reciprocal preference behavior on carbon emission reduction supply chain operations, this paper constructs a non-reciprocal preference for manufacturers without government subsidies on the basis of considering the dynamic impact of product carbon emission reduction levels on consumer demand. There are five differential game models, namely the non-reciprocal preference model for manufacturers with government subsidies, the reciprocal preference model for manufacturers without government subsidies, the reciprocal preference model for manufacturers with government subsidies, and the centralized mode. Carbon emission reductions are used as state variables to solve the optimal trajectory of supply chain emission reduction, comparing the carbon emission reduction levels of manufacturers and suppliers and the government's subsidy coefficient under different models, and using centralized decision-making as a benchmark to explore the impact of government subsidies and manufacturers' reciprocal preference behavior on supply chain carbon emission reduction levels and profits. Research shows that the reciprocal preference behavior of manufacturers will not only improve the profits of the manufacturers themselves, but also the profits of upstream suppliers. Government subsidies to supply chain members can improve the level of carbon emission reduction and profits in the supply chain, but government subsidies will weaken the reciprocal preference behavior of manufacturers.

In the remanufacturing supply chain, brand owners may choose to cooperate with contract manufacturers (i.e., CM) through outsourcing mode or authorization mode. For example, apple not only outsources both new product manufacturing and used one remanufacturing activities to Foxconn, but also allows Foxconn to resell remanufactured ones in the market in China, i.e., authorization mode. However, in USA, Apple still sells both new products and remanufactured ones in the market, namely, outsourcing mode. Motivated by these observations, traditional wisdoms try to answer the questions why the brand owners have different choices under information symmetry. In practice, the brand owner has advantages over the CM in market information due to nearness to the customers. To bridge the gap between the previous studies and the practice, we study brand owners' choice in remanufactured one sale modes under information asymmetry through the game-theoretic model. We find that:1) The brand owners have no incentives to share market information with the CM. 2) Whether the brand owners' preference on authorization or outsourcing mode depends on CM's sale cost and accuracy of information forecast under information asymmetry. To be special, (i) the brand owner prefers the outsourcing mode with low market prediction accuracy and high contract manufacturer's sales cost. Otherwise, the brand owner switches to the authorization mode. (ii) The expected profit of the contract manufacturer is always higher in the outsourcing mode. In addition, the brand owner and contract manufacturer will select the same sales mode when the brand's market forecasting ability and contract manufacturer's sales ability are both low.

Formation control of multi-agent systems has become a hot topic of interest for domestic and international scholars because of its wide application in military, aerospace, and biological fields. In practical applications, when the system is subject to external disturbances such as environmental noise, the controller cannot form the expected formation by using the relative state information of the leader-follower. To solve this problem, this paper investigates the leader-follower formation control problem for a class of nonlinear multi-intelligent systems with external disturbances. Firstly, a disturbance observer is designed to compensate the external disturbance. Secondly, a fully distributed control protocol is given using an adaptive approach. Then, the distributed control protocol is proved to be able to achieve the formation control of the system by selecting the appropriate parameters. Finally, the validity of the protocol is verified by simulation examples.

This paper studies customer balking behavior in Markovian queues with E-limited service rule and single vacation. In this system, there are no more than Φ customers can be served in a service period, so this service policy combines the features of both a limited service system and an exhaustive service system. In view of whether the system information is observable to customers, we consider two types of information levels:The observable case and the unobservable case. By establishing the linear cost-reward model and solving it, we get customers' equilibrium balking strategies and their socially optimal balking strategy in the unobservable case. In the observable case, customers' equilibrium balking threshold exists and is unique. In the unobservable case, customers' equilibrium joining rate is always higher than their socially optimal joining rate. Moreover, both the customers' equilibrium balking thresholds and their equilibrium/socially optimal joining rate are positively correlated with the value of Φ.