جستجوی مقالات مرتبط با کلیدواژه « شبیه سازی » در نشریات گروه « مدیریت »

According to Article 16 of the Knowledge-Based Production Leap Law, all industries that consume more than 2 megawatts of electricity must use 5% of their electricity consumption from renewable energy within 5 years. The model is optimized from the transient simulation method using Transis software, using the test design method, with the help of the response surface method. Two independent factors, the area of the solar panels and the power of the diesel generator have been selected as the main variables, and then the total electricity consumption, the total gas consumption, the total diesel fuel consumption, as well as the return on investment have been selected as the economic answer for optimization. It shows that increasing the area of solar panels with a low slope increases the investment return period. On the other hand, increasing the power of the diesel generator to about 2000 kilowatts helps to reduce the investment return period. But increasing the power of the diesel generator from 2000 to 3000 kilowatts increases the period of return on investment. Optimization using the response surface method showed that the optimal point occurs in the panel area of 11716.89 square meters and in the diesel generator power of 1986.69 kilowatts, the return on investment is 1.612 years, the results showed that the maximum value of the utility function is 0.725. which is a number very close to the maximum possible value (that is, the ideal state whose utility function is equal to 1

The main objective of the present study was to design a simulation model for development of organizational citizenship behavior (OCB) in Gas Company of Yazd province. A mixed method (qualitative and quantitative) approach was carried out in this research which was applied in terms of purpose and descriptive-analytical in terms of nature and method. In the qualitative step, the statistical population included university faculty members, managers, assistants, and experts of Yazd Gas Company, and in the quantitative part, it included university faculty members. Moreover, in the qualitative part, snowball sampling was performed until reaching theoretical saturation, and in the quantitative part, it was done by judgmental sampling. The data collection tools were interviews and questionnaires. In the qualitative section, using thematic analysis method, the effective factors on OCBs were identified. Then, the identified effective factors were prioritized using the fuzzy Delphi method, and finally, in the quantitative section, the organizational citizenship behavior development model was simulated using agent-based modeling approach. The data analysis led to the identification of 50 initial codes, 16 sub-themes and 4 main themes as below: individual, managerial, organizational and environmental factors. According to our results, managerial factor was recognized as the most effective factor. The simulation results illustrate that the presented model can provide an appropriate assessment of the future development of OCB in Gas Company of Yazd province

Adequate comprehension of the challenges and influential elements of the religious tourism sector is necessary for its positive development. In this regard, the present research was conducted to present a model that can simulate the development of religious tourism in Yazd province by considering the influential factors. A mixed method (qualitative and quantitative) was carried out in this study, and the research method was applied in terms of purpose and descriptive-analytical in terms of nature. The statistical population of this research included 12 theoretical and experimental experts. Questionnaires and interviews were used to collect data with non-random and purposeful sampling. In the qualitative section, the main and sub-categories of religious tourism development in Yazd province were identified using the thematic analysis method. Then, in the quantitative part, the identified influential factors were prioritized using the interpretive structural modeling (ISM) method. Finally, the criteria obtained from the qualitative research analysis were simulated using the agent-based modeling (ABM) method. Based on the research results, 35 initial codes, 12 sub-themes, and six main themes (religious tourism policies, economic, infrastructure, environmental empowerment, marketing, and cultural) were identified. Religious tourism policies were recognized as the most influential factor. Also, the results showed that at the end of the simulation period, the rate of religious tourism development in Yazd Province had reached 70%. Based on the findings of this study, it is recommended that tourism managers give particular attention to the influential factors that have been identified as having a significant impact on the development of religious tourism.

Recent advances in computers, networking, and telecommunications offer new opportunities for using simulation and gaming as methodological tools for improving crisis management. Videos can be used to present scenario updates to players in “newscast” format and to present pre-taped briefings by experts to players. Organizations responsible for crisis management are already using such technologies in constructing crisis management systems (CMSs) to coordinate response to a crisis, provide decision support during a crisis, and support activities prior to the crisis and after the crisis. The findings of the present study reveal that if designed with gaming in mind, the CMSs could be easily used in a simulation mode to play a crisis management game. Such a use of the system would also provide personnel with opportunities to rehearse for real crises using the same tools they would have available to them in a real crisis. In this paper, we provide some background for the use of simulation and gaming in crisis management training, describe an architecture for simulation and gaming, and present a case study to illustrate how virtual environments can be used for crisis management training.

The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.

The aim of the research is "designing a smart dynamic model of preventive net using simulation in interaction with production" based on the documentation of textile and clothing industries under the title of dynamic preventive net model. In order to calculate the dynamics of the system, Vansim software and research data were prepared based on a sample of 2000 data and reports from the textile and clothing industries during the years 2016 to the end of 2014 and the textile factories of Borujerd as the location of the project on a semi-annual basis. The results of the research show that the growth rate of "working environment on the net" has reached the lowest growth rate of 1.2% in 2016 and 3.5% in 2018 and a higher growth of 6% in 2014. The growth rate of "Internet technology" has reached an average growth rate of 1.2% in 1396, 5% in 1398, and a higher growth of 8.5% in 1400. The dynamic growth rate of the variable "Strategy in Net" has reached the maximum growth rate of 1% in 2016, 6% in 2018, and a higher rate of growth in 2014, i.e. 9.5% (optimal state).

In this paper, we study a production system that is subject to network failures and produces perishable goods. We assume that the system has preventive and corrective maintenance activities and can return defective items for rework. Our objective is to find the optimal production rate that minimizes the total cost of production, inventory, spoilage, and maintenance over a long planning horizon. We consider the uncertainty of machine failures and use discrete event simulation and ARENA.14 software to estimate the performance measures of the system. We also use data envelopment analysis to evaluate the efficiency of the system and identify the best scenario. The results show the effectiveness of our proposed model.

Emergency evacuation is one of the first stages of crisis management, which should be done in the shortest possible time and can have a great effect in reducing the death rate caused by the occurrence of danger. So the purpose of this article is to evaluate the emergency evacuation time of Mehrabad Airport in emergency situations through the simulation of emergency population evacuation strategies.

The research method is descriptive-analytical, in terms of solving the combined problem and the type of explanatory results. Collecting field and documentary information has been done. The statistical population includes 53 specialists, academic staff and graduate students. Random sampling and Cochran's formula were used. After conducting the interview and completing the questionnaire, the scenarios with a maximum of two incompatible factors were obtained from the Wizard software, and then the fifth scenario and two modes A and B were modeled in the Any Logic software.

The simulation results have shown. The evacuation time in the fifth scenario is higher than the other scenarios because the inspection room itself has a gate that reduces the speed of people leaving and increases the time required for people to leave. The results show that in case B, the time has increased compared to case A, in fact, in case A, 3600 people leave the place in 98 minutes, and in case B, the same number of people leave the place in 105 minutes. The reason for the increased time in mode B is because only the obstacles on the path are removed and the door is not added.

It can be concluded that only removing the obstacles is not an efficient method to reduce the evacuation time and the emergency door should also be added to the model. Also, according to the fifth scenario, the resilience of airport hall number 2 is not suitable in emergency situations because in the event of a crisis and an increase in congestion, the level of fear and speed is very high. In fact, in the event of a crisis, the airport in question is able to safely evacuate when the number of people exceeds 1000, since the number of people in normal conditions is 2000. Unlike the previous researches that had a one-dimensional look at the issue of emergency evacuation, this article has a mixed approach.

This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate of the system and the minimization of the total cost of reducing mean processing times and the total buffer capacities with respect to the optimal values of the mean processing time of each product in each workstation and the buffer capacity between workstations. For this purpose, in order to configure the structure of the mathematical model, Simulation, Design of Experiments and Response Surface Methodology are used and to solve it, the meta-heuristic algorithms including Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Ranked Genetic Algorithm (NRGA) are implemented. The validity of the multi-objective mathematical model and the application of the proposed methodology for solving the model is examined on a case study. Finally, the performance of the algorithms used in this study is evaluated. The results show that the proposed multi-objective mathematical model is valid for optimizing unreliable production lines and has the ability to achieve optimal (near optimal) solutions in other similar problems with larger scale and more complexity.

Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the chain. Adding effectiveness indicators along with LARG indicators and using the basics of the dynamic system to improve the efficiency of the supply chain is one of the innovations of this study. At first, by using research literature and studies, 12 headings of indicators were selected as LARG-E indicators. Then, with the Fuzzy Delphi method, the relationships and importance of each of these components were determined, and more important variables were modeled for further investigation. With using the concepts of dynamic systems, causal loops were drawn. Then, to check the function of the model, dynamic hypotheses were developed with the opinion of experts. In the next step, the flow diagram of the model and also the validation tests of the proposed model were done. Finally, by examining the outputs obtained from the proposed scenarios, it was found that most of variables have better behavior in LARG-E approach.

The purpose of this article is to model variables and scenarios affecting emergency evacuation during crises such as war and earthquake. The statistical population includes 160 specialists, academic staff and graduate students. The research method is descriptive-analytical. Random sampling method and Cochran's formula was used. Analysis has been done based on Wizard, Any Logic and Anp software. 8 scenarios with a maximum of two incompatible factors are considered for modeling in Any Logic. The more critical scenario obtained from the simulation was selected and the solutions were checked in the Anp software. Previous researches have not explained the simulated scenarios with the scientific method. We have used decision-making techniques and combined them with simulation to select solutions and scenarios. The evacuation time in the fifth scenario is longer than the other scenarios and we considered this scenario more critical. The results of Anp show that the criteria of adding doors and removing obstacles with weights of 0.287 and 0.262 have been ranked the highest. According to the normalized weight in the sub-criteria, in the criterion of time, the escape time in the corridors and stairs (with a weight of 0.65), in the cost, executive dimension (with a weight of 0.608), in the ability to execute, the ability to direct the operation. (with a weight of 0.8), in environmental effects, impact on the public (with a weight of 0.705) and in guarantee of traffic, the status of traffic management (with a weight of 0.756) have been ranked highest.

In this paper we try to simulate the life cycle of the electricity industry using the agent-based simulation method. For this purpose, 5 Agents were mentioned and they were simulated by Anylogic software .Then, four scenarios were investigated with experts' opinions. In the first scenario, it is assumed that the attractiveness of gas power and combined has been reduced and the attractiveness of the other two power has been added, the result of this scenario is the increase in hydroelectric power production, which is not cost effective due to the lack of water resources for the country. In the second scenario, with the arrival of a new technology, the household consumer decreased by 40%, and hydro and steam power with a capacity of 40% were working in the power generation cycle, the result of this scenario is the reduction of fuel consumption and also the shortage of electricity produced relative to the electricity consumption. In the third scenario, it is assumed that the consumption rate of all consumer factors has decreased, which results in the lack of investor factor investment. the fourth scenario assumes that all consumers' consumption is constant, as well as keeping the attractiveness developed by the government steady. As a result, the capacity of electricity generation has increased, but we are still facing power shortages.

Due to the effect of random factors such as machine failure on the competitiveness of production organizations and the importance of production planning, failure-prone manufacturing systems have emerged to deal with uncertainty. In order to maintain a competitive market share and increase productivity and safety, industrial systems have resorted to a maintenance strategy to reduce failure rates and increased reliability. Increasing production capacity, providing more flexibility and ensuring customer satisfaction in terms of quantity, quality and timing have made the use of subcontracting with a revenue sharing approach a viable option in this study. In this research, a network of machines with relationship limitation and failure and accidental repair is considered. To prevent shortages, intermediate buffers and a final buffer are used. Another important parameter is determining the optimal frequency of preventive maintenance, which results in minimizing the cost of preventive and corrective maintenance and repairs. The goal is to determine the optimal production rate and preventive maintenance variables and subcontractor variables. Discrete-event-simulation is used for this purpose. After modeling in Arena, the best values of decision variables are obtained in the opt-quest platform, which leads to a 22.5% reduction in total system costs.

Increasing researches, interests of researchers and industrial managers in the field of supply chain and environment, has necessitated the study of green supply chain network systems. In the present study, first, by reviewing the research literature and interviewing the experts in the ceramic tile industry, the factors affecting the success of the green supply chain were identified and the dynamical analysis of the problem was performed by using the systems dynamics method. For this purpose, available and documented information and expert opinions during the 10-year period simulation have been used. Systems dynamics is a powerful tool for modeling complex structures such as supply chain networks and provides useful information about the interaction of key system parameters. The developed model is implemented with VENSIM software and the impact of different policies is simulated and analyzed. The results indicate that strengthening factors of human resource skills, supervising the implementation of green rules and regulations, and suppliers will directly increase the success of green supply chain management; In the meantime, supervising the implementation of laws and regulations is known as the most effective factor. On the other hand, the variable order for green production is very important for the survival of green supply chain. This model and its accompanying simulation can be used as a practical decision support system for decision makers and managers of organizations so that they can make the best decisions according to their environmental or company conditions.

Today, customer attraction ability has come to be known as a competitive advantage in different organizations. Taking this into account, organizations must deal with the problem of demand reduction by adopting a strategy that enables them to retain existing customers and attract new ones. Therefore, in the present study, the principles and components of system dynamics were used to investigate the performance of Sepah Bank in this field. Employment of system dynamic modeling for customer attraction purposes in a financial institution is one of the innovative aspects of the study. 11 main indicators of organizational performance extracted from the research literature were used for this purpose. In the presented model, the structural relationship and the significance of each variable were determined by experts. Afterwards, the system dynamics concepts were used to present (in causal loop diagram) the effect of these factors on the rate of customer attraction through banks and advertisement. In order to account for the functions of the proposed model, the researcher then examined the variables in three scenarios to determine the effectiveness of each under different conditions. Finally, the proposed scenarios showed that using the optimal scenario, one can improve customer attraction rate by 20% through the pre-determined model relations. The results of the study can be used toformulate customer attraction strategies in Sepah Bank.

One of the most important problems involved insurance companies is insurance products pricing. In recent actuarial researches, fuzzy random variables have been used to consider uncertainty of economics parameters in insurance products pricing. Due to the effects of interest rate uncertainty on the insurance industry and especially life insurance, in this article, fuzzy random variables are implemented to consider interest rate uncertainty and calculate premiums for different types of life insurance products. Also, considering that the life table of Iran has been written based on the demographic information of this country and has been communicated to insurance companies to use, the results of using this table on fuzzy insurance premiums of different types of insurance policies have been compared with the life table TD88-90 previously used by insurance companies.

In this study, the fuzzy interest rates are used to define fuzzy discount functions and premiums of life insurance products is calculated.

In this paper, we have implemented fuzzy set theory to model interest rate for calculating premiums of life insurance products. Research findings were presented and analyzed for (term and whole) life insurances, endowments and life annuities using the interest rates announced in the supplement of Regulation No. 68 for Iranian life Insurance products. The premium calculations have been performed for Life table of Iran, which recently has been issued to be used by insurance companies, and life table TD88-90, which has previously been used by insurance companies.  Our findings based on Life table of Iran for a life annuity shows that all possible values of the premium for a 57-year-old person are in the interval [3.741, 4.384] and the deterministic amount of premium is 4.045. Also, the net premiums for the average risk aversion mode (β =0.75) is 4.212. Also, the effect of changes in β and insured age on premium amounts for different types of life insurance products has been studied and analyzed.  Furthermore, all calculations based on life table TD88-90 has been done and is compared with those based on Life table of Iran. Theoretically, the mortality probability of an x-year-old person according to the Life table of Iran is higher than the mortality probability of this person based on the life table TD88-90. So, the premiums calculated for this person based on the Iranian table for term insurance and endowment insurance are less and for life annuity is more than the premium calculated based on Table TD88-90. This can also be seen based on the findings of this article. On the other words, our findings based on table TD88-90 shows that all possible values of the fuzzy premium for a 57-year-old person are in the interval [3.575, 4.257] and the deterministic amount of premium is 3.896. Also, the net premiums for the average risk aversion mode (β =0.75) is 3.988. Also, these results were compared with the random method, which indicates the validity of the proposed fuzzy method.

Interest rates fluctuate over time due to changes in monetary, fiscal and foreign exchange policies, and this fluctuation can affect the determination of premiums, reserves and liabilities of insurance companies. This is especially important for life insurance products due to their long-term nature and the possibility of higher interest rate fluctuations during the policy period. Therefore, it is necessary to be considered the interest rate risk and uncertainty in life insurance products by the regulator and insurance companies. In this regard, using the fuzzy interest rate, the permitted range for the interest rate can be considered that insurance companies, taking into account their risk aversion, to determine the amount of premium in the desired period.JEL Classification: G22, C02, C63.

Advances in transportation technology and knowledge in recent years have provided different solutions to improve the transportation situation.One of the best solutions to solve traffic problems in big cities is to develop a high-speed bus system High capacity. In the present study, we have modeled and evaluated the performance of high-speed buses after development. For this purpose, first the capacity and service level of the study area in the current situation was determined. Then the capacity and service level of the area was determined after the addition of the express bus line. This was done due to the change in free flow velocity due to changes in some parameters of determining the level of service, such as reducing the width of the street, reducing the speed of traffic, marginal park, and so on. Finally, the current condition of the studied route and the condition of the route after the implementation of the high-speed bus line were simulated and compared in the software. The status of traffic parameters is getting worse. But the capacity of the route will increase by more than 20%. Therefore, due to the increase in the movement capacity of citizens due to the creation of high-speed bus lines, the development of public transport is necessary for private passenger cars, despite the deterioration of traffic parameters.