Evolutionary Simulation Research Articles

Evolutionary Kinetic Monte Carlo Simulation of Anisotropic Wet Etching of Sapphire at Different Concentrations and Temperatures

Evolutionary Kinetic Monte Carlo Simulation of Anisotropic Wet Etching of Sapphire at Different Concentrations and Temperatures

Climate mitigation under S-shaped energy technology diffusion: Leveraging synergies of optimisation and simulation models

Transforming global energy systems is critical for climate change mitigation and requires overcoming not only techno-economic, but also socio-technical hurdles. The main tools to analyse challenges in these two domains are integrated assessment models (IAMs) and transition theories or models, respectively. Despite a surging interest in integrative research that leverages complementarities in order to include social constraints into IAMs, both approaches are often confined to their own disciplinary background and practical integration studies of existing models are scarce. Here I demonstrate the feasibility of model integration by a bi-directional soft-link that merges the strengths of a neoclassical intertemporally optimising IAM with one global region, and a technologically and regionally highly resolved, evolutionary simulation model of S-shaped technology diffusion in the power sector. The new model iteratively converges to a stable equilibrium via two time-dependent coupling variables: carbon prices and renewable energy shares. The results for a 2 °C scenario show that due to gradual technology diffusion, energy transition challenges are exacerbated and incur higher economic losses. I discuss the potential of coupling existing models as an option to combine insights from different disciplinary perspectives to energy transitions.

Management Policy of Farmers’ Cultivated Land Abandonment Behavior Based on Evolutionary Game and Simulation Analysis

Agricultural land abandonment is a complex, multidimensional, and nonlinear global phenomenon driven by multiple factors and has contrasting impacts on agrobiodiversity, the environment, and society. Appropriate management strategies on abandoned cultivated land are helpful in maintaining food and ecological security. However, there are few studies on the management of cultivated land abandonment from the perspective of stakeholders. Based on the stakeholder perspective and focusing on the two main modes of farmland abandonment management, namely, “transfer-oriented management” and “condition-improved management”, this study constructs two evolutionary game models to analyze the interest conflicts, decision-making behaviors and interest game foci of different subjects in the two management modes. Simulation analysis is conducted to verify the equilibrium results of the evolutionary game to find the key problems in abandonment management and put forward corresponding management policies. This study reveals the internal mechanism of abandonment management, thus providing a theoretical basis for the classified management of abandoned cultivated land.

Emergence of kinship structures and descent systems: multi-level evolutionary simulation and empirical data analysis.

In many indigenous societies, people are categorized into several cultural groups, or clans, within which they believe they share ancestors. Clan attributions provide certain rules for marriage and descent. Such rules between clans constitute kinship structures. Anthropologists have revealed several kinship structures. Here, we propose an agent-based model of indigenous societies to reveal the evolution of kinship structures. In the model, several societies compete. Societies themselves comprise multiple families with parameters for cultural traits and mate preferences. These values determine with whom each family cooperates and competes, and they are transmitted to a new generation with mutation. The growth rate of each family is determined by the number of cooperators and competitors. Through this multi-level evolution, family traits and preferences diverge to form clusters that can be regarded as clans. Subsequently, kinship structures emerge, including dual organization and generalized or restricted exchange, as well as patrilineal, matrilineal and double descent systems. These structures emerge depending on the necessity of cooperation and the strength of mating competition. Their dependence is also estimated analytically. Finally, statistical analysis using the Standard Cross-Cultural Sample, a global ethnographic database, empirically verified the theoretical results. Such collaboration between theoretical and empirical approaches will unveil universal features in anthropology.

A Dynamic Equilibrium Mechanism of Core Layer Interests in the Mobile Medical Platform Ecosystem.

In recent years, with the development of the mobile Internet, big data, and cloud computing, the mobile medical platforms such as Ding Xiang Yuan aggregating platform ecological resources have played an irreplaceable role in improving efficiency, optimizing resource allocation, and even promoting the transformation and upgrading of the medical industry. Despite all this, most mobile medical platforms in China still face many problems, including the immature business model, the stagnation of the interaction of knowledge and information among platform members, and the weak platform competitiveness. Based on a review of the platform and commercial ecosystems, this paper adopts the evolutionary game method and simulation to analyze the evolutionary stability strategy of operators, partners, and users in the core layer of the platform during preflow and postflow periods of a mobile medical platform, hence, to construct a beneficial dynamic equilibrium model of a platform business ecosystem under the optimal decisions made by all parties involved in the platform: the goal in the early stage (preflow period) is to increase platform user flow. Hence, the knowledge/information sharing of platform users is needed to enhance platform's visibility. While in the late period (postflow period), when the platform user flow reaches a certain scale, platform's goal is to promote revenue, which relies mainly on the pricing strategy. It is critical to promote the stability of the platform and the dynamic balance of interests at the core layer in the pricing process. This paper applies the platform business ecosystem theory and the evolutionary game theory to mobile medical platform development, contributing theoretically and practically in the following: (1) providing a more solid theoretical support for the mobile medical platform research and enriching the theoretical framework of the platform business ecosystem; (2) proposing the dynamic equilibrium model based on the optimal decisions of the platform core layers, which help to reveal the inherent law of the evolution of the mobile medical platform; (3) providing policy suggestions and management implications in constructing an appropriate business ecosystem and achieving sustainable development in mobile medical platforms.

Evolution enhances mutational robustness and suppresses the emergence of a new phenotype: A new computational approach for studying evolution.

The aim of this paper is two-fold. First, we propose a new computational method to investigate the particularities of evolution. Second, we apply this method to a model of gene regulatory networks (GRNs) and explore the evolution of mutational robustness and bistability. Living systems have developed their functions through evolutionary processes. To understand the particularities of this process theoretically, evolutionary simulation (ES) alone is insufficient because the outcomes of ES depend on evolutionary pathways. We need a reference system for comparison. An appropriate reference system for this purpose is an ensemble of the randomly sampled genotypes. However, generating high-fitness genotypes by simple random sampling is difficult because such genotypes are rare. In this study, we used the multicanonical Monte Carlo method developed in statistical physics to construct a reference ensemble of GRNs and compared it with the outcomes of ES. We obtained the following results. First, mutational robustness was significantly higher in ES than in the reference ensemble at the same fitness level. Second, the emergence of a new phenotype, bistability, was delayed in evolution. Third, the bistable group of GRNs contains many mutationally fragile GRNs compared with those in the non-bistable group. This suggests that the delayed emergence of bistability is a consequence of the mutation-selection mechanism.

An Evolutionary Game Simulation of a Composite Subsidy Policy to Promote Military-Civilian Integration: A National System of Innovation With Chinese Characteristics

Collaborative innovation involving military and civilian actors is a key component of National Systems of Innovation. It is an approach that is explicitly promoted in China under the name of Military-Civilian Integration. To more effectively promote Military-Civilian Integration, it is necessary to study the impact of government subsidies on enterprise-level behavior. The research reported in this paper analyzes a composite subsidy policy’s influence on the cooperative innovation behavior of military and civilian enterprises with game theory. First, during the early stage of development, an R&D subsidy can stimulate firms to invest in technological innovation, but it harms the long-term and stable development of civil-military cooperation by encouraging free-riding behaviors. Second, as military-civilian integration continues and deepens, the input-output rate of the R&D will increase, and this makes the role of tax subsidies increasingly relevant. Third, the composite application of scale and tax subsidies will be most effective in reinforcing innovation during the Industrialization Stage. Fourth, further simulations show an apparent heterogeneity in the responses of the military enterprise and the civilian enterprise to the three kinds of subsidy that we have considered. Civilian enterprises are more sensitive to subsidies, while military enterprises are more sensitive to technology spillovers. Therefore, the government should build a military-civilian integration platform to share resources in ways that maintain security confidence and improve the R&D input-output rate. The government should strengthen confidentiality management, training, and risk prevention and control measures for military-civilian integration projects, to reduce the risk of technology spillover.

Tea industry's sustainable development: based on participants' tripartite evolutionary game and numerical simulation

Tea industry's sustainable development: based on participants' tripartite evolutionary game and numerical simulation

Tea industry's sustainable development: based on participants' tripartite evolutionary game and numerical simulation

Tea industry's sustainable development: based on participants' tripartite evolutionary game and numerical simulation

Evolutionary Game and Simulation Analysis of Low-Carbon Technology Innovation With Multi-Agent Participation

Low-carbon technology innovation (LCTI) is an effective way to solve the problem of global climate change and reduce carbon emissions. Therefore, using evolutionary game theory, this research constructs a three-party evolutionary game model of LCTI involving the government, enterprises, and consumers. Moreover, this research investigates the strategic choices of the three parties in the process of LCTI, discusses the stability of the equilibrium point. In particular, it analyzes the influence of different factors on the strategic choices of the three parties through numerical simulation. The results indicate that, 1) the government, enterprises, and consumers are affected to different degrees by each other’s initial willingness; 2) the intensity of government regulation, innovation subsidies, and carbon tax rates have different effects on enterprises and consumers; 3) consumers are more sensitive to innovation subsidies. These results could provide references for enterprises to promote the development of LCTI.

Evolutionary Game and Simulation Research of Blockchain‐Based Co‐Governance of Emergency Supply Allocation

Recently, with the spread of COVID‐19 pandemic, emergency supply allocation system is drawing more and more social attention. Emergency supply allocation system is an important part of emergency governance system. It reflects social organizations’ credibility, public safety, and the modernization level of social governance. However, emergency supply allocation system still has some problems, such as information asymmetry, different desires of participants, unreasonable allocation, and so on. At present, it is widely accepted that the advantage of blockchain in co‐governance could be of great help in solving above problems. And in order to distinguish the effect of blockchain to the emergency supply allocation, the paper builds a tripartite evolutionary game model among the government, social organizations, and the public to analyse the impact of blockchain platform on emergency supply allocation. The simulation analysis shows the following: (1) The strategy choices of the government have a crucial impact on the evolution and stability of social organizations’ strategies. It needs a long‐term process to guide social organizations practicing active allocation, and the government should accelerate to build the blockchain platform to promote this process. (2) With the help of blockchain platform, the increment of penalty intensity of the government is conductive to increasing the probabilities that social organizations practice active allocation and the government practices strict supervision. (3) Blockchain platform has a significant impact on social organizations’ choice for active allocation in many aspects, such as the positive and negative effects of social organizations, effect’s increasing multiple, and the cost of the public informing. In the end, some suggestions are presented to improve the co‐governance of emergency supply allocation.

Evolutionary Game and Numerical Simulation of Cultivated Land Protection Policies Implementation in China

The effective implementation of cultivated land protection policies (CLPP) has important practical significance for improving China’s food security and ecological security. The central government, local governments, and farmers have mutually restricted and influencing interest relations. At the same time, the codes of behavior of multistakeholders also affect the implementation of CLPP in the social system. Therefore, this article discusses the behavioral tendencies and game relationships of relevant stakeholders in the implementation of CLPP from the perspective of evolutionary games and portrays a cognitive decision-making process closer to reality. Finally, numerical simulation reveals the key variables that affect the stability strategy. Results show the following: (1) As the main body of system supply, the central government should reconstruct the political achievement evaluation system and improve the status of the effective implementation of cultivated protection policies in the political achievement evaluation of local governments. (2) The central government should increase incentives for local governments to implement CLPP and increase penalties for violations to improve the effectiveness of policy implementation. (3) To optimize the actual implementation of CLPP, increasing awareness of farmers’ rights protection, reducing rights protection costs of farmers, and increasing the constraints on the flexible implementation of CLPP are necessary.

The Evolutionary Game Analysis and Optimization Algorithm of Electric Vehicle Cell Innovation Diffusion Based on a Patent Pool Strategy

A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear. We introduced an innovation diffusion channel model comprising different players with patent licensing relationships and market competition relationships following evolutionary game analysis and simulation. We found the interlinked factors that influenced evolutionary stable strategies with a sensitivity test on all factors to identify the important and unimportant factors. To achieve the maximum return for the players, an optimization algorithm was introduced to find the maximum weighted object function. The decision and policy makers could focus on important factors such as improving the technology’s competitive advantages, delivering more profits to its licensees with reasonable licensing fees, and finding the best patent pool strategy with the support of the optimization algorithm to balance the competition relationships and patent licensing relationships between players.

Tripartite Evolutionary Game and Simulation Analysis of Coal Mining Safe Production Supervision under the Chinese Central Government’s Reward and Punishment Mechanism

In recent years, although coal mine accidents in China have decreased, they still occur frequently. Most previous studies on the evolutionary game of safety mining are limited to a focus on system dynamics and two-party game problems and lack a spatial graphic analysis of strategy evolution. The parameters adopted are too few, and the influencing factors considered are too simple. The purpose of the paper is to introduce more parameters to study which will have an important impact on the strategy choices of participants and the evolution path of the strategy over time. We construct a tripartite evolutionary game model of coal mining enterprises, local governments, and central governments. As our method, a payment matrix of participants and replicated dynamic equations is established, and we also implement parameter simulation in MATLAB. In summary, we found that the reward and punishment mechanism plays an important role in safe coal mining. Specifically, (1) intensifying rewards and penalties for coal mining enterprises and local governments will help encourage coal mining enterprises to implement safe production measures and local governments to implement central government safety supervision policies. However, increased rewards will reduce central government’s willingness to adopt incentive strategies. (2) The central government’s reward for coal mining enterprises’ safe production must be greater than the increased cost of safe production to encourage enterprises to implement such production. Economic incentives for local governments must be greater than the benefits of rent-seeking; only then will local governments choose to strictly implement supervision policies. (3) Increasing sales revenue and rent-seeking costs of coal mining enterprises can also encourage them to implement safe production. Therefore, a well-designed reward and punishment mechanism will change the behaviour of coal enterprises and improve the probability of safe production. The research presented in this paper further works on improving safe coal mining production and designing reasonable reward and punishment mechanisms.

PREFABRICATED HOUSING SUBSIDY ANALYSIS IN CHINA BASED ON AN EVOLUTIONARY GAME MODEL

Prefabricated housing and cast-in-site housing are two alternatives for selection by developers and customers. The government, as the policy maker, creates incentive policies to encourage developers and customers to choose prefabricated housing. This paper aims to analyze the subsidy mechanism to theoretically confirm the subsidies’ scopes, amounts and end times through an evolutionary game model and simulation. In the game model, government subsidies affect the interactions between developers and customers in the decision-making process. The findings are as follows: 1) The developer housing subsidy can lower the housing price, while the customer housing subsidy can increase the price; 2) The government should first offer the developers a larger subsidy amount during the early development stage and then offer the customers a smaller subsidy amount later; 3) The government should determine the end time based on the proportion of developers and customers who choose prefabricated housing; 4) A higher prefabrication ratio may not always improve the development of prefabricated housing, and there is an optimal production scale that creates the best development situation. The empirical analysis shows that this model can help the government develop reasonable and optimal subsidy policies within the limit of budget to stimulate developers and customers.

University–Industry Collaborative Innovation Evolutionary Game and Simulation Research: The Agent Coupling and Group Size View

Based on the evolutionary game theory, this paper explores the evolutionary stable strategy (ESS) of university-industry collaborative innovation. By utilizing MATLAB software, the analysis of the influence of agent coupling degree, group size, and government policies on the stable evolution of university-industry collaborative innovation is taken into account, while simulating. Our findings indicate that, first, agent coupling degree is positively and nonlinearly related to the stable evolution of university-industry collaborative innovation; second, when an enterprise's size is equal to university's, group size is more significant to the stable evolution of university-industry collaborative innovation than agent coupling degree; third, when a group size of an enterprise and university is different, the combinations of agent coupling degree and group size have various effects on the stable evolution of enterprise group and university group; and fourth, government policies have a significantly positive impact on the stable evolution of university-industry collaborative innovation, and incentive measures are more effective than punitive ones. Research conclusions have developed the relationship among university-industry collaborative innovation agents, expanded the boundary of the stability study of collaborative innovation, and provided new ideas for improving the effectiveness of government innovation policies.

Evolutionary game analysis of coal enterprise resource integration under government regulation.

Resource integration of coal enterprises is conducive to reducing pollution and carbon emissions, thus alleviating environmental problems such as global warming. Government regulation has a great influence on enterprise behavior. Therefore, it is necessary to analyze the strategies of government and coal enterprises in resource integration. Based on the perspective of government regulation, this paper discusses how to guide and restrict coal enterprises to conduct resource integration behavior, and whether the government supervises this behavior. First, through empirical research, government regulations of coal enterprises are given practical policy implications. Second, using evolutionary game and simulation technology, from the perspective of government regulation, we explore the complex behavioral interaction mechanism between the dominant and inferior coal enterprises, the mechanism between the government and coal enterprises, and analyze the impact of key factors on the dynamic evolution process. Finally, the sensitivity analysis of the selected parameters is discussed in details, which provides useful decision-making suggestions for the government and enterprises. In addition, this paper further analyzes the impact of different government policies on coal enterprises' green innovation strategies. Results demonstrate that (1) when the power gap between enterprises is large, the probability of dominant enterprises choosing resource integration converges to 1, while the probability of inferior enterprises converges to 0. Therefore, government regulations are invalid for inferior enterprises; (2) the combination of government regulations can help improve the efficiency of coal enterprises' strategic choices. With the increase in the intensity of government rewards and punishments, the probability of enterprise resource integration evolves from 0 to 1; (3) excessive government regulations make the choice between the government and coal companies tend to swing, because the probability of the two is between 0 and 1. Therefore, excessive government regulations cannot effectively achieve resource integration and government regulation. (4) The government subsidy strategy is less effective than the government's pollution penalty strategy in promoting the green innovation of enterprises. Our research shows that the government should choose different policy combinations and intensities to regulate resource integration according to the market power of coal enterprises, which provides theoretical reference and practical guidance for the government to regulate corporate resource integration behavior.

Evolutionary game theoretic resource allocation simulation for molecular communication

Molecular Communication (MC) is an emerging technology using molecules to transfer information between nanomachines. In this paper, we approach the resource allocation problem in Molecular Nano-networks (MCN) from the perspective of evolutionary game theory. In particular, we consider an MCN as an organism having three types of nodes acting as a sensor, relay, and sink, respectively. The resources are distributed among the nodes according to an evolutionary process, which relies on the selection of the most successful organisms followed by creating their offspring iteratively. In this regard, the success of an organism is measured by the total number of dropped messages during its life cycle. To illustrate the evolution procedure, we design a toy problem, and then solve it analytically and using the evolution approach for comparison. We further simulate the performance of the evolution approach on randomly generated organisms. The results reveal the potential of evolutionary game theory tools to improve the transmission performance of MCNs.

The route problem of multimodal transportation with timetable: stochastic multi-objective optimization model and data-driven simheuristic approach

PurposeDistribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.Design/methodology/approachMonte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.FindingsNumerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.Originality/valueThe impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

Mobile Gene Sequence Evolution within Individual Human Gut Microbiomes Is Better Explained by Gene-Specific Than Host-Specific Selective Pressures.

Pangenomes—the cumulative set of genes encoded by a population or species—arise from the interplay of horizontal gene transfer, drift, and selection. The balance of these forces in shaping pangenomes has been debated, and studies to date focused on ancient evolutionary time scales have suggested that pangenomes generally confer niche adaptation to their bacterial hosts. To shed light on pangenome evolution on shorter evolutionary time scales, we inferred the selective pressures acting on mobile genes within individual human microbiomes from 176 Fiji islanders. We mapped metagenomic sequence reads to a set of known mobile genes to identify single nucleotide variants (SNVs) and calculated population genetic metrics to infer deviations from a neutral evolutionary model. We found that mobile gene sequence evolution varied more by gene family than by human social attributes, such as household or village. Patterns of mobile gene sequence evolution could be qualitatively recapitulated with a simple evolutionary simulation without the need to invoke the adaptive value of mobile genes to either bacterial or human hosts. These results stand in contrast with the apparent adaptive value of pangenomes over longer evolutionary time scales. In general, the most highly mobile genes (i.e., those present in more distinct bacterial host genomes) tend to have higher metagenomic read coverage and an excess of low-frequency SNVs, consistent with their rapid spread across multiple bacterial species in the gut. However, a subset of mobile genes—including those involved in defense mechanisms and secondary metabolism—showed a contrasting signature of intermediate-frequency SNVs, indicating species-specific selective pressures or negative frequency-dependent selection on these genes. Together, our evolutionary models and population genetic data show that gene-specific selective pressures predominate over human or bacterial host-specific pressures during the relatively short time scales of a human lifetime.