جستجوی مقالات مرتبط با کلیدواژه "شبیه سازی" در نشریات گروه "مدیریت"

In order to calculate the employment trend in Iran, the aim of the article is to optimize the employment trend in Iran for the years of implementation of the sixth economic, social and cultural development program (1396-1400). For this purpose, firstly, using the Gauss-Seidel algorithm, the system of dynamic and non-linear macrometric equations and the quantitative goals of the sixth development program, the employment process in the country was simulated. Then, the optimal trend of the working population was calculated from the minimization of the welfare loss function of the policymaker by programming and implementing an open-loop algorithm and solving the Bellman equations. The obtained results showed that achieving higher employment requires controlling inflation at lower rates as well as achieving a higher economic growth rate. The findings of this research are compatible with the theory of new Keynesians such as Gerish, Clarida, Gertler, Menkiu, Walsh and Taylor regarding the necessity of simultaneously reducing inflation and increasing production. Therefore, the jump in production and curbing inflation can be the optimal control of employment and business at the level Make the goal possible. Based on this, the targeting of macroeconomic indicators in the available (possible) territory, complete monetary and financial discipline, independence of the central bank and the use of stochastic optimal control theory in the targeting of development programs are among the policy recommendations of this article.

Ensuring the safety and health of human resources is one of the most important tasks that every organization must deal with in order to maintain its competent workforce. The results of the occupational health and safety management system lead to the prevention of work-related injuries and illnesses to workers and create a healthy and safe working environment. But the implementation of this system and its maintenance is not always successful so that the organization can benefit from it. The current research, using the system dynamics method, analyses the factors affecting the successful implementation of an ISO 45001 occupational health and safety management system in water and wastewater companies and it simulates a model of factors affecting ISO 45001. The statistical population of the current research is experts in the field of quality of water and waterwaste companies and universities. First, the factors affecting the implementation of ISO 45001 were extracted from the research literature, and then by interviewing experts, the necessary variables were identified and the causal-flow anf flow charts of factors were mapped using Vansim software. At the end, the system dynamics model of ISO 45001 factors system was simulated. The results of the model simulation showed that when implementing ISO 45001 and maintaining this system, the support of senior managers, the selection of a good consultant for the organization in order to reduce the complexity of procedures and instructions, and also pay attention to the skill level of internal auditors. plays a role. Also, the duration of the consultant's cooperation with the organization is effective in the successful implementation of this system.

The war game is an applied discipline aimed at serious games, while being professionally distinguished from futures studies, has its own special requirements and scientific community. Alongside the distinction, similarity of the two disciplines is significant, especially by non-educational games at the political and strategic levels. The problem is that if the commonalities and areas of synergy between the two disciplines are not well understood, the futile competition between the experts of the two disciplines will increase. For this purpose, in addition to archival studies and holding focus group meetings consisting of wargaming, futures studies and strategic studies activists, qualitative content analysis was used to professionally infer the relationship between the two fields.It is possible to see the convergence of two disciplines in theoretical foundations, having common goals and areas of practical synergy, as well as the possibility of synergy in the field of method. These two have practical synergy with each other in cultivating agile thinkers and decision makers, interdisciplinary and transdisciplinary teaming, seeking participation from divergent thoughts, problem-oriented environment analysis, knowledge sharing, and upskilling in methods and technics. In the future, it is necessary to examine more closely the relationship between the scientific and administrative processes of the two fields for the educational and research synergy between the scientific centers of war games and futures, as well as the development of common tools and systems, which is reflected in the development of the idea of “futures lab”.

The electricity sector plays a crucial role in the country's economy. Therefore, any disruptions in the supply chain of this industry can result in the loss of economic benefits and decrease the competitiveness of industries dependent on this sector. The industry structure analysis of the electricity sector has shown that the lack of proper relationships between entities involved in the supply of goods and equipment leads to disruptions in the electricity supply chain. On the other hand, the specific political and economic conditions of the country, the presence of natural disasters, and high levels of change in the Middle East region have had significant impacts on increasing uncertainty at various levels of the supply chain in this sector. Considering the high uncertainty in the procurement of components in this industry, this study focuses on presenting a set of scenarios for replenishing goods in the supply chain entities of this sector. To achieve this, a probabilistic four-echelon model consisting of a supplier, distributor, retailer, and customer was presented to minimize total inventory costs and the ratio of unmet customer demand based on the (R, Q) policy. Furthermore, by searching organizational documents, interviewing industry experts, and utilizing warehouse management software, data for the model was collected. Subsequently, through experimental design, initial solutions were provided for the differential evolutionary algorithm, and based on this algorithm, different values for reorder points and order quantities were determined. By employing simulation methods, the model's objective values were estimated, and the set of solutions was illustrated in a Pareto chart. Research findings have shown that increasing the average inventory levels of retailers' warehouses leads to a decrease in the proportion of unmet customer demand. This occurs when different reorder point values for two retailers have high levels, but considering the probabilistic demand function, the order quantity can vary. On the other hand, reducing ordering and inventory costs leads to an increase in unmet customer demand. In other words, when reorder point values and low order quantities lead to inventory reduction, customer dissatisfaction increases. The Differential Evolution Algorithm used in this study has accelerated the process of finding solutions and improved model efficiency. This algorithm considers values between high and low levels of reorder points and order quantities, presenting multiple objective function values. Utilizing simulation methods to estimate the probabilistic objective functions employed in the model has increased the speed of executing multiple scenarios, aiding in cost reduction and model execution time. Based on the results of this research, electric equipment with high innovation should have a low reorder point and a high order quantity in the supply chain. This is because the short product lifespan renders the product obsolete along the chain, lacking customer demand and consequently increasing the chain's costs. The computational results of this study indicate that a 105% increase in inventory leads to a 104% increase in customer satisfaction and a 95% decrease in lost sales costs. However, considering the high purchasing costs and large product volume during ordering, a scenario aligned with financial conditions and warehouse capacity should be selected for chain entities.

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

The development of innovative ecosystems leads to the overall enhancement of innovation and creativity in countries, subsequently contributing to their economic development. Since the presence of uncertainty and external disruptions affects the performance of the innovation ecosystem, the existence of resilient innovation ecosystems that can withstand disruptions and maintain their performance under any circumstances is of great importance in the current complex and changing environment. Therefore, this research calculates the resilience index of key players in the power industry innovation ecosystem through a case study, using three indicators: "lost performance level," " Robustness," and "recovery speed." The results show that, the innovation ecosystem had a moderate level of lost performance index in the face of the simulated disruption and is not in a favorable state in terms of recovery speed and Robustness. Based on this, policymakers and managers of this ecosystem need to consider measures to enhance its resilience and take effective decisions and strategic planning to improve its response to potential disruptions. Additionally, by utilizing the simulated results, they can observe the impact of implemented policies on the resilience of the studied ecosystem.

Various techniques and approaches have been presented to solve multi-objective decision making problems under different assumptions. The STEM technique is also one of the most widely used techniques for dealing with this group of problems, especially for solving multi-objective linear programming (MOLP) models. In the current research, a new approach has been proposed as the development of the mentioned method. In this regard, the second phase of the method is integrated with the simulation process and the concept of utility function has been used in order to determine the probability of selecting targets. For each of the selected targets, several random adjustment rates are defined. Random selection of satisfactory functions based on their utility and using simulation tools, will "create diversity in the selected objectives for adjustment". Also, by considering different and random adjustment rates for selected functions, while facilitating the decision-making process and providing an analytical report to the decision-maker, it will be possible to apply "different levels of satisfaction" of the decision-maker. A three-objective problem with five constraints, is solved using the proposed method and its results are presented. The results indicate that applying the above changes will lead to solving some of the basic limitations of this method that have been mentioned in previous studies. Comparing the proposed technique with the basic method, shows the overall superiority of the proposed method, especially in the criteria related to interaction with the decision maker.

There is a direct relationship between the number of machinery in any industrial problem, their costs of purchase,  and the space they occupy. Accordingly, due considerations about the constraints are required in space and budget. Workshop production problems under uncertainty conditions including more than two pieces of machinery are regarded as NP-hard. Therefore, using common research in operation techniques, one cannot embark upon modelling and finding the optimal answer for such problems. Hence, this study aims to propose a conceptual mathematical model for the problem of industrial production. The research problem involves cost limitations while working out the solution through simulation studies.

Design/methodology/approach: 

First a mathematical model has been proposed for workshop production with cost and space constraints. Then by enlisting the help of Arena software, 14 simulation models have been designed for machine ‘m’ and work ‘n’ of different production sequences. Finally, by solving a numerical model example, the problem of nearing the optimal condition of the problem, considering minimizing the objective function of the tardiness and earliness costs, has been resolved. This measure has been adopted to determine the optimal number of machinery, considering work prioritization laws in work cells by executing the model and scatter search algorithm and designing relevant experiments.

Solving a numerical example considering the default number of machinery and the LPT optimization method resulted in the best answer when the total tardiness and earliness costs were intended. In contrast, in the case of increasing the number of machineries, both the LPT (longest process time) and CR (critical ratio) methods led to the best answers with the help of dispersed search algorithms in simulation studies. The results included the cost and space constraints.

Research implications:

 One of the prominent features of simulation is that with the minimum distance between the problem and the real world (not removing the limitations and complexities for solving the problem, which is usually done by removing the facts in other problem-solving methods, to reduce the complexity and the possibility of solving the problem) problem-solving and decision-making scenarios are applied. This helps managers in decision-making. Most of the time, the physical study of systems is very difficult and costly, or even impossible; therefore, an alternative model should be used to study the system.

Originality/value: 

A careful investigation of previous research and relevant literature reveals that none of the studies in the literature have simultaneously dealt with the problem of the number of machinery in conditions of cost and space limitations. Therefore, the present study incorporated the mentioned constraints in the scheduling problems and adopted simulation problem-solving methods. It resulted in delving and enriching the subject further.

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.

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.

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.

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.