Stochastic Evolutionary Model Research Articles

Evolutionary Carrier Selection for Shared Truck Delivery Services

With multiple carriers in a logistics market, customers can choose the best carrier to deliver their products and packages. In this paper, we present a novel approach of using the stochastic evolutionary game to analyze the decision-making of the customers using the less-than-truckload (LTL) delivery service. We propose inter-related optimization and game models that allow us to analyze the vehicle routing optimization for the LTL carriers and carrier selection for the customers, respectively. The stochastic evolutionary game model incorporates a small perturbation of customers' decision-making which exists due to irrationality. The solution of the stochastic evolutionary game in terms of stochastically stable states is characterized by using the Markov chain model. The numerical results show the impact of carriers' and customers' parameters on the stable states.

How to Enhance Data Sharing in Digital Government Construction: A Tripartite Stochastic Evolutionary Game Approach

Digital government construction is a complex system project, and data sharing is its governance niche. Cross-sectoral data sharing is the core issue of improving governance capacity in the construction of digital governments. Aimed at the dilemma of insufficient data sharing across departments, according to evolutionary game theory (EGT), we refined the game relationship between the data management department and the different government functional departments participating in cross-department data sharing. We used white Gaussian noise as a random perturbation, constructed a tripartite stochastic evolutionary game model, analyzed the stability of the stochastic game system and studied the influence of the main parameters on the evolution of the game system with the help of numerical simulation. The results show that there exists a positive stable point in the process of cross-department data sharing. The external effect of data sharing can be improved by enhancing the investment in data sharing by government functional departments. The accumulation of interagency trust relationships can gradually eliminate the differences in data sharing among different departments. The coordination mechanism of government data sharing and the construction of the “good and bad reviews” system can form an internal and external adjustment mechanism for functional departments and the data management department and can promote multiple departments to participate in cross-department data sharing more actively.

Three-Party Stochastic Evolutionary Game Analysis of Supply Chain Finance Based on Blockchain Technology

In the process of accounts receivable financing under supply chain finance, the phenomenon of accounts receivable forgery and default have caused great pressure on the supervision of financial institutions. We consider the integration of blockchain technology with a supply chain finance platform around the fraudulent default phenomenon in supply chain finance receivables financing and construct a three-party stochastic evolutionary game model among financial institutions, core enterprises, and Micro, Small, and Medium Enterprises (MSMEs). Firstly, we use Ito^’s stochastic differential equation theory to analyze the conditions for the stability of the behavior of game subjects. Secondly, we use numerical simulations to quantitatively analyze the impact of the regulatory strength of financial institutions, the information sharing of the blockchain platform, and the change of incentive parameters on the strategy choice of game subjects. Through the above analysis, we conclude that the information-sharing incentive coefficient promotes financial institutions to choose to connect to the blockchain platform, and the information-sharing risk coefficient and the regulatory intensity have the opposite effect on the blockchain platform construction. Meanwhile, the allocation of incentive shares has a significant influence on the core enterprises. Finally, we give priorities and directions for adjusting the relevant parameters to provide recommendations for financial institutions to regulate the financing process more effectively.

Analysis of collaborative urban public crisis governance in complex system: A multi-agent stochastic evolutionary game approach

As the world economy is leaping forward, countries have been exposed to the constant threat of public crises. Accelerated urbanization has currently led to a proliferation of urban public crisis events. Conventional governance methods become ineffective under the effect of the highly uncertain and dynamic nature of urban public crisis events. Accordingly, this study primarily aims to facilitate the construction of a collaborative multi-agent alliance in urban public crisis governance. Thus, evolutionary game theory is combined with system dynamics, Gaussian white noise stochastic disturbance terms are introduced to model the complex characteristics of urban public crisis events, and evolutionary game models and stochastic evolutionary game models are built for three types of groups (i.e., local governments, enterprises, and the public) to study the evolutionary process of group strategy choice behavior with or without central government supervision. The result of this study suggests that under the effect of the complexity factor, the central government's dynamic reward and punishment mechanism plays a role of in reaching a facilitative and stable alliance for collaborative urban public crisis governance. Furthermore, contributions, unresolved issues and vital challenges are identified. In this study, a solid basis is laid for future research and widespread use of collaborative urban public crisis governance, which provides a reference for stakeholders in the field of urban public crisis governance.

How to promote the hierarchical diagnosis and treatment system: A tripartite evolutionary game theory perspective.

Due to the disorderly access to medical care and inefficient use of health resources, the advancement of the hierarchical diagnosis and treatment is more valued in promoting health system reform. Hence, this article integrates prospect theory into an evolutionary game model of the local government health departments, the medical institutions, and the patients in the system promotion of the hierarchical diagnosis and treatment. The simulation shows the specific influencing mechanism of the psychological perceived value of game subjects. Then by introducing the stochastic evolutionary game model, the system promotion under different medical cultures is also discussed in detail. The results indicate that for local government health departments, the amount and duration of financial subsidies are the key factors influencing the game system's evolution. For medical institutions, participating in the hierarchical diagnosis and treatment system is relatively beneficial. For patients, the recovery rate in primary hospitals matters more than the cost of treatment. Changes in the risk sensitivity coefficient will cause the equilibrium of the game system to change. However, changes in the loss avoidance factor do not change the equilibrium and only have an impact on the speed of convergence. With the health departments' intervention, patients in rural medical culture are more inclined to support the hierarchical diagnosis and treatment system than those in urban or town medical culture. Therefore, in order to promote the hierarchical diagnosis and treatment system, this article recommends that more attention should be paid to the regulatory role of health departments and the participation improvement of medical institutions and patients.

Research on digital sharing mechanism of agricultural science and technology resources considering collaborative innovation capability

The digital sharing of agricultural scientific and technological resources is the key to promoting agricultural scientific and technological innovation. Explore the strategic mechanism for the digital sharing of agricultural scientific and technological resources, reveal the law of their behavioral evolution, and provide theoretical guidance for the practice of digital sharing of agricultural science and technology resources. Introducing the perspective theory of perceived utility to replace expected utility, constructing a stochastic evolutionary game model for the sharing parties and demand parties of agricultural science and technology resources, analyzing the dynamic evolution rules of both sides of resource sharing, and analyzing the key factors affecting the stability of agricultural science and technology resource sharing through numerical simulation.

Cross-regional collaborative governance in the process of pollution industry transfer: The case of enclave parks in China

To promote the effectiveness of cross-regional collaborative governance of pollution firm transfer, a stochastic evolutionary game model among three sectors (flying out parks, pollution firms, and flying in parks) was proposed. According to the three policy goals, three paths of collaborative governance were investigated using numerical simulations. Our findings focus on the following three aspects: (i) If policymakers want to urge more parks and pollution firms in the three sectors to choose a cooperation strategy, additional relocation subsidies from superior governments for pollution firms have the most remarkable effect. However, excessive subsidies will push flying out parks to inhibit the transfer of pollution firms. (ii) If policymakers intendto urge parks and pollution firms to cooperate quickly, increasing the environmental costs of firms will play key role. Notably, even if the environmental costs are low, they can still considerably and positively affect choosing a transfer strategy of for pollution firms. (iii) If policymakers expect defection parks and pollution firms to be as few as possible during the regulation process, the cost-sharing mechanism with only two sectors (flying in parks and flying out parks) is invalid. Introducing higher-level departments or other sectors for cost-sharing to escape the current dilemma is necessary.

Evolution with mass extinction on Td+

We propose a stochastic model for evolution through mutation and natural selection of a population that evolves on a Td+ tree. We think of this model as a way of describing the evolution fitness landscape of a population. We obtain sharp and distinct conditions on the set of parameters for extinction and survival.

Evolution dynamic of intelligent construction strategy of coal mine enterprises in China

The intelligent construction of coal mining enterprises is the fundamental strategy to prevent and curb major coal mine accidents, and the core technical support to realize the high-quality development of the coal industry. Considering the intelligent construction of coal mining enterprises enabled by emerging information technologies such as 5G and artificial intelligence, this paper constructs a Moran process stochastic evolutionary game model of intelligent construction of coal mining enterprises. Based on the fixed point probability of the Moran process, the probability of successful invasion of the "intelligent construction" strategy and the "traditional production" strategy in the limited coal mining enterprise group is calculated. By comparing the probability of individual fixed point and the probability of neutral mutation, the dominant condition of the strategy under strong selection and weak selection is obtained. The research shows that external stochastic factors, the number and scale of enterprises, the intensity of capacity replacement and the cost-benefit of intelligent construction are the main factors affecting the intelligent construction behavior of coal mining enterprises. When the intelligent construction of coal mining enterprises is in the cultivation period, the intelligent construction of underground coal mines dominated by stochastic factors can be effectively promoted by increasing the intensity of capacity reduction replacement. For the open-pit coal mine dominated by expected payoffs, reducing the number of mining rights and improving the concentration of open-pit coal mining industry will have a better effect on promoting its intelligent cultivation process. When the intelligent construction of coal mining enterprises is in the mature stage, with the improvement of the cost and benefits of intelligent construction, "intelligent construction" strategy will become a general consensus of coal mining enterprises. In addition, this paper analyzes the relevant parameters through specific examples to verify the effectiveness of the conclusions, which provides a scientific basis for effectively accelerating the intelligent construction of coal mining enterprises and promoting the transformation and upgrading of the coal industry.

ЗАСТОСУВАННЯ СТОХАСТИЧНИХ ЕВОЛЮЦІЙНИХ РІВНЯНЬ З МАРКОВСЬКИМИ ПЕРЕКЛЮЧЕННЯМИ У НЕКЛАСНИЧНИХ СХЕМАХ АПРОКСИМАЦІЇ ДЛЯ ПОБУДОВИ ТА АНАЛІЗУ МОДЕЛІ ІНФОРМАЦІЙНОЇ БОРОТЬБИ

Analysis of the state of the art asymptotic properties of stochastic evolution models reveals that a complete theory is still to be worked out. Well understood are the deterministic models and stochastic ones which are given by differential equations, in particular with Markov switchings and perturbations in the classical schemes of averaging or diffusion approximation. Thus, it seems natural to develop a theory of evolution equations with Markov switchings and random perturbations in nonclassical approximation schemes. We consider stochastic equations with Markov switchings and impulse perturbations under the conditions of Levy and Poisson approximation. The results obtained in the present research may be divided into two parts. In the first part, we consider some prelimit evolution models with a small normalization parameter. We find the form of the limit generators for the impulse processes and the dynamical system in the schemes of the Poisson approximation and the Levy approximation. It is important that in this part of the thesis the asymptotic behavior of the limit process is concluded with the help of the analysis of parameters of the prelimit system. Further, in the second part we explore, analyze and provide the peculiarities of constructing the information struggle model described by such stochastic evolution. The new pattern is decoded as the effect of rare events quickly changing certain perceptions of a large number of people. As a result, the number of supporters of different ideas makes stochastic jumps, which one can see using non-classical approximation schemes.

Stochastic Evolutionary Game Analysis on the Strategy Selection of Green Building Stakeholders from the Perspective of Supply-Demand Subject Populations

In construction industry, the research and development (R&D) and application of green building technologies (GBTs) are crucial to promote the development of green buildings. From the perspective of supply-demand subject populations, this paper discusses the dynamic evolution process of strategy between individuals within construction enterprise populations and between construction enterprise populations and consumer populations. Firstly, based on Moran process, the stochastic evolutionary game model of construction enterprises adopting independent innovation strategy was constructed to obtain the conditions for the dominance of independent innovation strategy. Next, the bimatrix game model of construction enterprise populations and consumer populations was constructed to obtain the equilibrium frequency of the joint strategy. Then, the influence laws of the change of parameters on game were discussed through numerical simulations. The results show that (1) reducing the cost of independent R&D cost, reducing the spillover effect coefficient, increasing the loss of technology introduction, and increasing R&D subsidies for independent innovation construction enterprises are all conducive to IIS becoming an evolutionary stable strategy. (2) The marginal effect of IIS increases with the decrease in the spillover effect coefficient, the increase in the loss of technology introduction of construction enterprises, and the increase R&D subsidies. (3) The smaller the mutation rate is, the greater the cross-price sensitivity coefficient is, the greater the green sensitivity coefficient is, the greater the probability of government active encouragement is, and the more dominant (production of green buildings, purchase of green buildings) is. Finally, relevant measures and suggestions are proposed.

The stochastic evolutionary game analysis of public prevention and control strategies in public health emergencies

PurposeThe COVID-19 epidemic is still spreading globally and will not be completely over in a short time. Wearing a mask is an effective means to combat the spread of COVID-19. However, whether the public wear a mask for epidemic prevention and control will be affected by stochastic factors such as vaccination, cultural differences and irrational emotions, which bring a high degree of uncertainty to the prevention and control of the epidemic. The purpose of this study is to explore and analyze the epidemic prevention and control strategies of the public in an uncertain environment.Design/methodology/approachBased on the stochastic evolutionary game model of the Moran process, the study discusses the epidemic prevention and control strategies of the public under the conditions of the dominance of stochastic factors, expected benefits and super-expected benefits.FindingsThe research shows that the strategic evolution of the public mainly depends on stochastic factors, cost-benefit and the number of the public. When the stochastic factors are dominant, the greater the perceived benefit, the lower the cost and the greater the penalty for not wearing masks, the public will choose to wear a mask. Under the dominance of expected benefits and super-expected benefits, when the number of the public is greater than a certain threshold, the mask-wearing strategy will become an evolutionary stable strategy. From the evolutionary process, the government’s punishment measures will slow down the speed of the public choosing the strategy of not wearing masks. The speed of the public evolving to the stable strategy under the dominance of super-expected benefits is faster than that under the dominance of expected benefits.Practical implicationsThe study considers the impact of stochastic factors on public prevention and control strategies and provides decision-making support and theoretical guidance for the scientific prevention of the normalized public.Originality/valueTo the best of the authors’ knowledge, no research has considered the impact of different stochastic interference intensities on public prevention and control strategies. Therefore, this paper can be seen as a valuable resource in this field.

Numerical Simulation of the Lightning Leader Development and Upward Leader Initiation for Rotating Wind Turbine

Lightning accidents seriously threaten safe operation of wind turbines because the influence mechanisms of wind turbine rotation on corona and upward leader initiation are, so far, not clear. A three-dimensional stochastic evolution model of the lightning downward leader was established by combining the dielectric breakdown model and the lightning current shunt method, according to which the charge density distribution of leader branches was determined. The corona and leader initiation mechanisms of rotating wind turbine were studied based on the 3D drift and diffusion model of ion flow in the neighboring space of a rotating wind turbine. The results show that due to blade rotation, the charged particles are unevenly distributed near the blade tip and the contours are in a strip-like shape. As the rotating speed increases, the blade tip is more susceptible to initiating corona discharge. Combining the three-dimensional stochastic development model of the lightning downward leader and ion distribution model near a rotating wind turbine, the initiation direction of the upward leader was analyzed, and in 66% of cases, the initiation direction of the upward leader on the blade tip was on the back side of the blade rotation.

Stochastic stability in the large population and small mutation limits for coordination games

We consider a model of stochastic evolution in symmetric coordination games with $ K\ge 2 $ strategies played by myopic agents. Agents employ the best response with mutations choice rule and simultaneously revise strategies in each period. We form the dynamic process as a Markov chain with state space being the set of best responses in order to overcome difficulties that arise with the large population. We examine the long run equilibria for both orders of limits where the small noise limit and the large population limit are taken sequentially. We characterize an equilibrium refinement criterion that is common among both orders of limits.

Modeling the industry perspective of university-industry collaborative innovation alliances: Player behavior and stability issues

Many firms find it challenging to develop innovations, evidenced by the ever-mounting number of university-industry research alliances. This study examines the strategic choices of actors who participate in collaborative innovation alliances involving partnerships between industry and universities (U-I) based on a stochastic evolutionary game model. White noise was introduced to reflect uncertainty and the stochastic interferences caused by the differences between actors. Using the Itô stochastic differential equation theory, we analyze stability issues of player behaviors in the evolution of a collaborative innovation alliance. The results illustrate that improvements in innovation efficiency can contribute to U-I collaborative innovation alliances. High knowledge complementarity appears to be unbeneficial to the stability of these alliances, and controlling knowledge spillovers may suppress free-rider problems from both sides of the game. Our study contributes to innovation research by providing a decision-making reference for the design of U-I cooperation.

A Tripartite Stochastic Evolutionary Game Model of Complex Technological Products in a Transnational Supply Chain

A Tripartite Stochastic Evolutionary Game Model of Complex Technological Products in a Transnational Supply Chain

Large deviations and Stochastic stability in Population Games

<p style='text-indent:20px;'>In this article we review a model of stochastic evolution under general noisy best-response protocols, allowing the probabilities of suboptimal choices to depend on their payoff consequences. We survey the methods developed by the authors which allow for a quantitative analysis of these stochastic evolutionary game dynamics. We start with a compact survey of techniques designed to study the long run behavior in the small noise double limit (SNDL). In this regime we let the noise level in agents' decision rules to approach zero, and then the population size is formally taken to infinity. This iterated limit strategy yields a family of deterministic optimal control problems which admit an explicit analysis in many instances. We then move in by describing the main steps to analyze stochastic evolutionary game dynamics in the large population double limit (LPDL). This regime refers to the iterated limit in which first the population size is taken to infinity and then the noise level in agents' decisions vanishes. The mathematical analysis of LPDL relies on a sample-path large deviations principle for a family of Markov chains on compact polyhedra. In this setting we formulate a set of conjectures and open problems which give a clear direction for future research activities.</p>

Stochastic evolutionary game analysis of e-waste recycling in environmental regulation from the perspective of dual governance system

Due to the rapid popularisation and development of electronic products, recycling e-waste has become an issue which cannot be ignored. To facilitate the effective management of the recycling of e-waste, this paper constructed a tripartite Itô stochastic evolutionary game model to perform analysis of the complex game interaction between national government, local government and recyclers. Due to uncertainty in the external environment, Gaussian white noise was introduced into replicator dynamic equations, the random Taylor expansion was applied to solve the numerical approximations, certain critical values were determined so the system exhibited chaotic behaviour and numerical simulation was used to describe the dynamic evolution of tripartite. The results showed that the following: (1) The optimal evolutionary stability strategy indicated that national government should adopt positive supervision, local government should enforce environmental regulations and recyclers should choose qualified disassembly. This behavioural strategy would significantly improve the quality of e-waste recycling. (2) Enforcing environmental regulations is dependent on a subsidy-penalty coordination mechanism, whereby the subsidy is increased for qualified recyclers and there are default penalties for collusion. (3) Local government should cover more of the cost of environmental governance in order to avoid excessive costs which can decrease national government enthusiasm for positive supervision. Avoiding low costs could lead to free-riding behaviour from local government and collusion between local government and recyclers. (4) The uncertainty of the external environment impacts the decision-making of the tripartite participants. The stability of the equilibrium solution is related to the Gaussian white noise intensity and this can cause the equilibrium strategy to deviate from its original trajectory. This study will provide constructive suggestions for dual governments which will enable them to better formulate and implement environmental regulations while encouraging recyclers to participate in qualified disassembly more actively.

Three-Party Stochastic Evolutionary Game Analysis of Reward and Punishment Mechanism for Green Credit

To get rid of the development dilemma of green credit, we constructed a stochastic evolutionary game model of local government, commercial banks, and loan enterprises. We gave sufficient conditions for the stability of strategy based on the stability discriminant theorem of It o ^ ' s stochastic differential equation (SDE). Then, we discussed the impacts of incentive and penalty parameters on green credit. Through the above analysis, we got the following conclusions: (1) rewards and punishments always benefit green production and green credit, but increasing incentives is not conducive to the governments’ performance of regulatory duties; (2) punishments can better improve the convergence rate of players’ strategy than rewards; and (3) both rewards and punishments can exert an obvious effect in improving the changing degree of players’ strategy. Finally, we put forward some suggestions to optimize the green credit mechanism.

How to escape the dilemma of charging infrastructure construction? A multi-sectorial stochastic evolutionary game model

Providing effective charging infrastructure is an essential step in popularizing electric vehicles, which is conductive to improving pollution induced by traditional fuel vehicles and thus improving the environmental sustainability. The most crucial factor in escaping the dilemma of charging infrastructure construction lies in the synergies of multi-sectorial. This paper develops a stochastic evolutionary game model grounded on the strategy adoption of charging infrastructure construction involving governments (public), companies (private), and consumers (civil). We collect the data of Shanghai for simulation to compare the influence of strategy adoption. Our findings suggest that ⅰ) unlike the public and civil sector, in the current situation, the private sector will adopt the defector strategy quickly and lock in the defection state as time goes on; ⅱ) the additional cost effect caused by public-civil co-construction scenario is significant positive to the public sector but almost no impact on the civil sector; ⅲ) civil's strategy adoption has directional differences under two cost sharing scenarios (private-civil and public-civil) of charging infrastructures construction. In the private-civil scenario, if the cost of charging infrastructures construction is transferred to the civil sector, not only will it not change the private-sectorial defection state, but it will also cause civil sector to shift from cooperation to defection. However, at the same sharing ratio of the public-civil scenario, the civil sector is still willing to cooperate. ⅳ) reducing incentives of electric vehicles or increasing costs of internal combustion engine vehicles is necessary, which will not change the lock-in cooperation state of civil sector, and it can improve the cooperation willingness of publicsector.