agent based modeling

 The primary goal in emergencies is the complete evacuation of the crowd to save lives, but the behaviors of the crowd, their interactions with the physical environment, and the use of evacuation management strategies can affect its time, particularly in religious places. In this study, we aim to evaluate the impact of the crowd’s social dependencies and fear and the use of a phased evacuation strategy on the duration of emergency crowd evacuation in Bani Hashem Shrine.

This is a descriptive-analytical study using the agent-oriented approach and the integrated framework for crowd evaluation and evacuation. The pilgrims to the holy shrine of Bani Hashem on special days, such as Muharram and Arbaeen, constituted the study population. Based on plausible scenarios, crowd evacuation in emergency and non-emergency situations was simulated using Pathfinder software to evaluate the effects of social dependency, fear, and the use of a phased evacuation strategy on the duration of crowd evacuation.

To evaluate the effect of social dependency, simulations were conducted in four scenarios, with dependency rates of 5, 10, 15, and 20% of the population. The results showed an increase in the evacuation time by 623, 635, 651, and 675 seconds, respectively. To evaluate the impact of the fear factor, simulations were conducted in four scenarios, with fear rates of 5, 10, 15, and 20% of the population. The results showed that fear increased the evacuation time by 644, 675, 749, and 854 seconds, respectively. To assess the impact of phased evacuation strategy use, the simulation was carried out in three scenarios with evacuation delays of 45, 90, and 135 seconds. The results showed an increase in the evacuation time by 621, 632, and 647 seconds, respectively.

The duration of the complete crowd evacuation of the Bani Hashem shrine in normal and non-emergency conditions is 619 seconds. The crowd’s behaviors resulting from social dependencies and fear and the use of a phased evacuation strategy can increase the evacuation duration.

Microfinance as a predominant poverty alleviation strategy with the aim of lifting poor out of poverty, provides financial services to poor. This research examines the effect of using micro loans on the growth of people's income and lifting them from poverty line. Also, with regard to the financial aid to MFI, changing in years of donate and its effect on lifting people from poverty line are discussed. In addition, the effect of marketing and increasing the probability of sales as a complementary service of microfinance, in the growth of income is investigated. Therefore, this research, examines the effect of microfinance on increase income and lifting poor from poverty by considering two policies changing the number of years of donate to MFI and increasing the probability of selling the product.

In MFIs, the way of providing resources, different conditions of lending, as well as the interactions between people, and become member of MFIs and influencing receipting of loans, creates a complex environment. The heterogeneous characteristics and behaviors as well as the interactions between agents in a dynamic environment, cause the emergence of complex events that using agent-based modeling approach can help to understand and model. agent-based modeling is a simulation approach of a set of autonomous, independent and decision-making agents that are interconnected and tries to investigate the final results of a system by modeling the behavior of individual elements. In this research, agent-based modeling approach has been used.

The result shows the provision of microloans has increased people's income and provides the possibility of getting out of absolute poverty for most people. In this research, we considered the interest rate to be zero, the results showed the resorce of MFI based on savings and repayment of installments can increase, so that the number of paid loans even in the policy of 2 years donate increased. Therefore, by providing interest-free microloans and even limiting the duration of assistance, a sustainable microfinance MFI can be created. Also, the policy of changing the number of years of donate to MFI and increasing the number of years of donate from three years to four years does not have a significant effect on increasing people's income, and MFI will be able to continue based on savings and receiving repayment of installments, but increasing the number of years of donate will cause the number of loans so that by increasing years of donate to 2, 3 and 4, the number of loans paid is equal to 155, 221 and 278, respectively. Also, the results of modeling of increasing the probability of sale showed that in the scenario with the probability of 80% sales, the income of people and the number of people above the poverty line are much higher than the scenario of the probability of 60% sales. Totally, the modeling of the policies of changing the number of donate years to MFI and changing the probability of sales showed that more financial aid to MFI does not lead to more income of people and lifitin tehm from poverty line, but what causes more income is helping to marketing and sales product.

Reducing the number of donate years and using the released financial resources to create a market and increase the possibility of sales will make poverty alleviation policies more effective. In other words, if the financial resources of donate helps to create guaranteed markets or to form permanent markets, creates a greater leverage effect for increasing income of  members than the increase the number of donate years to MFI.

The increasing growth of electricity consumption in recent years has made its demand management a vital issue in the field of energy. One of the important actors in the field of electricity consumption are industries, which requires more attention to this field. In 2019, the country's electricity consumption in the industrial sector was 34.7%, therefore, it will be necessary to take measures to change the behavior of electric energy consumers in the industrial sector, especially during peak consumption times. For this reason, in line with global experiences, we can expect the consumption pattern in this sector to be revised by revising the tariff structures of the industrial sector. In this research, a new tariff structure has been proposed by replacing price-quantity packages instead of a fixed tariff at the time of peak consumption.Also, to measure the effectiveness of the proposed tariff structures, the results were evaluated for an industrial town with 62 subscribers in Mazandaran with an agent-based approach. The results obtained from the simulation show that by applying this structure to the subscribers, the average peak load demand can be reduced by 2.57% to 9.51%

Increasing operating profit is a challenge faced by pharmaceutical distribution companies. Most of the researches conducted in this field have a cost reduction approach. The online monitoring system is one of the effective methods that can be used for managers' decision-making and improving the performance of the pharmaceutical distribution chain with the approach of reducing costs and increasing revenues. To create this system, conceptual, mathematical and computer modeling is needed. The aim of this research is to develop a mathematical model of the online monitoring system to improve the pharmaceutical distribution system based on a conceptual model using a reinforcement learning approach. The mathematical model was derived based on the factor-based conceptual model and using the multi-factorial reinforcement learning approach. After extracting the mathematical model, the effectiveness of the model was validated by comparing the results obtained from the output of the mathematical model and the actual results in a pharmaceutical distribution company. The findings of the research showed that the developed mathematical model has the ability to continuously improve the goals, decisions and performance of the pharmaceutical distribution chain processes, according to the interactions and changes in the behavior of agents and the state of the environment.

In this study, the information security knowledge sharing model is presented from the integration of the theories of planned behavior, motivation, triandis and behavior change stages in an organization by combining the statistical method of structural equation modeling and agent-based modeling and simulation; Also, in this study, structural equation modeling has been used to build models as inputs for factor-based modeling and to improve and improve their reliability and validity. in other words; In this study, structural equation modeling has been applied for factor-based modeling. The data collection method is a questionnaire made by the researcher and collected by simple random sampling method. After testing the validity and reliability of the questionnaire, data was collected from 217 participants. Using SmartPLS3.2.6 and Anylogic software, hypothesis testing and simulation based on statistical results are analyzed in order to analyze the change of behavior over time. The findings have shown that the factors of the theory of planned behavior, including attitude, mental norms, perceived behavioral control and motivation theory, which include internal and external motivational factors, and the Triandis model, in order to facilitate the conditions, have positive effects on the stages of behavior change from It includes the stages of pre-reflection, reflection, preparation, action, maintenance and termination. In addition, the change in information security knowledge sharing behavior in the organization increases over time until reaching the end stage. The innovation of this study is factor-based modeling in order to test hypotheses over time along with the statistical method of structural equation modeling. In addition, the behavior change model has also been applied to analyze the behavior change stages of information security knowledge sharing. Knowledge sharing plays an important role in the field of information security; Because it has a positive effect on the awareness of employees' information security.

Due to the key role and importance of using agent-based modeling and simulation tools in various applications, such as urban management and planning, social networks, financial markets, traffic flows, and crisis management, it is worthwhile to evaluate and quantitatively compare these tools based on a well-defined standard framework. So far, several studies have reviewed and compared agent-based modeling and simulation tools from different aspects. However, none of the studies are quantitatively performed based on a well-known standard framework. To fill this research gap, in this paper, five of the most widely used agent-based modeling and simulation tools including AnyLogic, NetLogo, Repast, GAMA, and MASON were compared and evaluated based on the well-known ISO 25010 standard, regarding the quality in use, by Goal-Question-Metric (GQM) method. The evaluation results show that AnyLogic tools are of better quality than others, and this is due to the attractiveness of the tool from the user's point of view and less effort to develop an agent-based application compared to other tools.

The purpose of paper is to present a conceptual model of the IOT-based online monitoring system to improve the distribution system‌ of pharmaceutical, using the agent-based modeling approach. First, by reviewing the research literature and interviewing industry experts, the basic concepts are extracted and using the grounded-theory method, the conceptual grounded-theory model is compiled; finally, using the obtained model and performing the agent-based modeling steps, the conceptual model of the agent-based is extracted. Based on the findings, data quality, information and communication technology infrastructure, automatic measurement and evaluation, and automatic action and evaluation are among the factors affecting the IoT-based online monitoring system. Also, the agents of the organization, customers, suppliers, governance and information technology infrastructure, interact with each other and with the environment. Based on the results, the IoT-based online monitoring system is an effective way to improve processes, and decision makers can make smarter decisions with this approach.

The purpose of this paper is to suggest intervention routes to responsible institutions in order to prevent the diffusion of coronavirus. The covid 19 pandemic is the most effective disease since the beginning of 2020, which in addition to many deaths, has had many economic and social effects. Many researchers are trying to treat and develop a vaccine, but one of the most basic measures is prevention because prevention is the fastest way to reduce mortality and its negative consequences.

For this purpose, with the maximum use of minimal data in the country and considering the new rules governing the behavior of this virus, the evidence-based policy-making method and Agent-based modeling have been used, which includes four steps of simulator construction, calibration, Validation, and its use to estimate how the disease is evolving.

In order to determine the main factors affecting the prevention, four policy scenarios including general quarantine, non-intervention, passive intervention and intelligent intervention were examined. In simulating policy scenarios, the factors of movement rate and transmission risk change proportionally. The quarantine in an optimistic state itself includes four categories of scenarios based on different quarantine methods, and finally, the stop and treatment-related scenarios were also examined. The simulation results showed that a 50% reduction in the movement rate would lead to a reduction of more than 80% in the number of patients, and a 10% decrease in the transmission risk index would lead to a 30% reduction in the number of patients.

Finally, two factors of movement rate and transmission risk index were identified as the most important factors in the diffusion of coronavirus. Therefore, it is suggested that the responsible institutions focus on designing intelligent interventions related to the reduction of these two factors in order to reduce the prevalence of corona more quickly.

With the tremendous progress in communications in the world, the transformation and behavior of mobile operators and their digitalization, which in the past were only service providers, as well as the creation of different experiences for customers, is inevitable.

The purpose of this study is to create a hybrid simulation of system dynamics and agent based modeling in order to analyze the revenue of the first operator in the country to enter the field of digital platform and development of native applications. Using the model proposed in this article, first the need for operators to enter the digital arena and produce native applications was expressed. Then, the factors that affect the mobile ecosystem that affect the production of applications and the development of required platforms were described. Benefiting from hybrid simulation of system dynamics and agent based modeling, the income of mobile operator in entering and not entering the digital arena and producing native applications were examined.

The findings showed that with the entry of the operator into the field of production of native applications and the adoption of digital approach, consumers tended to use more data services, but due to different tariffs for data and voice, the operator's income up to 2 Next years will not change much.

Recently, imbalances in the electricity production and consumption in Iran, have caused critical situations at specific times of the year; meanwhile, the residential sector, with a 51 percent share, is the main reason for peak demand crisis. According to the international experiences, it can be hoped that by revising the residential electricity tariff structure, consumption pattern in this sector would be modified. Therefore in this study, according to the country’s ongoing projects and infrastructures, a new electricity tariff structure which is a combination of time-of-use and maximum-demand pricing, has been proposed. In the second part of this study, by developing an agent-based model and applying this tariff to residential consumers, their consumption behavior in peak hours is simulated. The results of these simulations, showed that by offering this tariff to consumers, the average demand of peak-hours can be reduced by 6.15 percent.

The purpose of this study was to develop an agent based model that could simulate the steel supply chain and estimate its production and consumption, taking into account the key factors of the steel industry. The approach of the present study is mixed (quantitative and qualitative). In the first part of the research (qualitative), the agents of the steel chain consumption model were obtained through interviews with experts using thematic analysis method. In the second part of the research (quantitative), a questionnaire was used to survey the causal relationships of the factors extracted from the interviews and the thematic analysis method, and then the relationship model was tested by the DEMATEL method. Finally, by using AnyLogic software and coding in Java language, a model of steel supply chain and its consumption was designed throughan agent-based  approach, and according to the opinion of steel industry experts, the model explanation process was also approved. The combination of agents identified in this study is consistent with the influence of factors on production, consumption, import and export of the steel chain in the proposed structural model.

With increasing competition and the pace of change, companies will face with a crisis focus on exploiting existing capabilities or exploring new capabilities [1]. To adapting to the speed of change, Companies must adapt ideas or processes, which lead to the development of new products or services in emerging markets, and they must use current capabilities to exploit existing products and services [2]. So, in today's world, we need ambidextrous organizations with the ability of managing two kinds of incremental and radical changes simultaneously , and the ability of doing two opposite works at the same time, which are: stability of the status quo and change [3]. Therefore, the purpose of the present study is to identify the dimensions of ambidexterity, characteristics of an ambidextrous bank and provide a model for decision making on ambidexterity dimensions of a bank based on agent-based modeling according to market scenarios. This simulation model has been run in AnyLogic software.

The purpose of this study is to introduce a method to improve innovation diffusion by using agent-based modeling. In this regard, an operational analysis to create agent-based modeling is investigated. agent-based model of this research is carried out in combination with the bass model. in this model, inputs include advertising effects and word-of-mouth effects estimated using the bass diffusion model. output of the model is also the total number of innovation adopters at each time step in the potential market that has been validated after the model has been correspond to real data (diffusion of television in Iran). to be more correspondent to real-world, the agent-based model is developed by preferential attachment-based network. after creating the model, the validation and verification were carried out by experiments and the operational analysis of the agent-based modeling. after model validation, we examine our method (using artificial innovators) for improving the diffusion of innovation. after validating the model, the proposed method for improving innovation diffusion through ten scenarios is investigated. in addition, a proposed criterion for analyzing the output of the innovation diffusion is presented, which is used to analyze the outputs. after the analysis, the method of artificial innovators was effective.