mohammad khalilzadeh

The purpose of the present study is to assess the risk in planning and launching the production of the cylinder block of the Shahin automobile. This research is exploratory, which seeks to determine the risk in planning and launching the production of the cylinder block of the Shahin automobile in the Saipa Company using the TOPSIS approach, risk matrix, and Monte Carlo expert system. For this purpose, by reviewing articles and interviewing experts, the conceptual model dimensions of economic benefit indicators, technology benefit indicators, and technology readiness indicators were identified, each of which had its sub-criteria. In this way, and using the TOPSIS method, rankings were given in each of the identified indicators. The results of the study showed that the most important criteria were obtained in the following order: comparative advantage, technological knowledge, top management support, certainty, profitability, security, rate of return on capital, necessary knowledge and skills, observability, compatibility, sufficient financial investment, IT standards, IT skills, complexity and technology infrastructure. Also, according to the results obtained from the sum of the coefficients in each dimension, the most important dimensions were identified, so that the order of the identified dimensions was technological benefits, organizational factors, economic benefits, and technological readiness. Furthermore, based on a Monte Carlo simulation, 11 different cases were examined, which showed the accuracy of the results about the severity of the identified risks.

The most important policymaker entity in the bank-centered economy of Iran is central bank of Islamic Republic of Iran which has always been trying to manage and improve macroeconomic indicators by applying monetary policies. However, investigation of Iran's economy after four decades shows that this country has always suffered from double-digit inflation rates and 15000-fold liquidity throughout this period, while GDP of Iran has grown only by two times during this period. This paper tries to evaluate the effect of monetary policies of central bank on macroeconomic indicators by analytical-descriptive and library method via combining system dynamics and fuzzy multi-criteria decision-making using Vensim and Super Decision software. Monetary policy instruments in this re-search include foreign exchange rate, deposits interest rate, facilities interest rate, required reserve ratio, and open market operations. Further, the macroeconomic indicators include inflation, liquidity, national foreign exchange value, and eco-nomic growth. The results indicated that the most important macroeconomic indi-cators in the country according to economic experts are "national foreign ex-change value" and "inflation". The most important tool for monetary policies of central bank is "foreign exchange rate". Indeed, in order to improve the economic misery index, this bank should take measures to improve the national foreign exchange value, then manage inflation and liquidity, and eventually adjust the banking interest rate

Power semiconductor devices are the most important components in power electronics applications. They are also the most fragile components of electronic circuits. A power semiconductor device's switching performance and protection depend on the gate drive circuit specifications. Therefore, choosing an appropriate gate-driver and designing its corresponding circuits is necessary. This paper is a technical review of the proper design of gate drivers for silicon power switches (like Si IGBT and Si MOSFET) in industrial power electronics applications. In this paper first conducts an overview of the main specifications of gate drivers for industrial power electronics applications. Then, concerning the protective role that a gate-driver can provide, crucial points of an effective design are discussed. Finally, a circuit is proposed to test the gate driver's short-circuit protection. The circuit is experimentally evaluated for three gate drives, and the results are discussed. A practical comparison of the protection performance of commercial gate drives ACPL-330J, ACPL331, and PC929 is also conducted.

In many legal systems based on direct or semi-direct democracy, some means of popular supervisory mechanisms, including popular initiative, referendum, and recall, are envisaged. Recall is one of the modern popular supervisory methods that, while identifying the representative body, tries to remove the incumbent before the end of his/her term of office. This practice is still unknown and not used in the constitutions of many countries, but considered highly beneficial in a democratic environment. The main question of the present study is the essence of this legal entity by studying it in the legal systems of several states and federal level of the US. For this purpose, in this article, after recognizing the background and classification of recall with regard to the types of monitoring, the mandatory conditions and typology of this process will be discussed. The typology of recall includes its sorts in terms of justified reasons or grounds, signature collection threshold to start the election, and the how of the filling the position of the ousted official or the recall election methods. In some cases, the legislature, taking into account the circumstances, by anticipating the grounds excludes this process from an exclusively political process, which requires the provision of reasons. As a categorizer, one of the distinguishing features of recall is that, unlike other constitutional supervisory tools such as expulsion and impeachment, it is exercised outside of the ruling forces and by citizens. This article tries to introduce the recall, its background and types, evaluation of the recall, a plan to modify the problems raised by the opposition, and finally the possibility of the recall at the federal level of the US legal system.

Contractor selection for a construction project is among the most important factors in achieving the project’s success. In Iran, contractors for construction projects in public sector are mainly selected according to Tender’s Law. Despite the fact that a quality assessment is implemented through a prequalification phase, however, in the final phase of the tender process, “the lowest bid price” criterion reigns and the contractor with the lowest proposed price is considered as the eligible contractor to whom the contract of the project is awarded. The prequalification phase eliminates many incompetent contractors from the competition process, but this does not lead to a considerable improvement in the quality of construction because no responsibility is established for a better performance and the winner of the contract keeps meeting the minimum requirements.Contractor selection by the lowest tender is one of the main reasons for quality shortcomings, weak performance of the contractor, cost and time overruns, increasing in change orders and claims, conflicts, dissatisfaction of the client, increasing in life-cycle costs and other disorders and may finally lead to the project failure (Zavadskas et al., 2008, El-Sayegh et al., 2019, Hasnain and Thaheem, 2016, Scott, 2006). To overcome this, some multi-criteria decision-making methods have been proposed by many researchers. As a proposal for reforming the tenders’ process in the context of Iran, in this paper, VIKOR method is used for ranking of the alternatives in which “the proposed price” criterion is added to the assessment criteria which are commonly used in the prequalification phase. An illustrative example from water industries in East Azerbaijan province confirms the applicability of the proposed method.

The automotive industry is one of the most competitive industries globally. Hence, a proper pricing policy is vital to be able to compete. This paper develops an automotive supply chain consisting of one manufacturer and one retailer, with two types of one product (Basic and Premium). The Premium type of the product is equipped with extra features and technologies to convince customers to purchase it at a higher price, while the Basic one without these features is sold at a lower price. Furthermore, the manufacturer is intervened by the government regulations which results in receiving subsidies or paying taxes. This paper develops a mathematical model to maximize profit in both centralized and decentralized systems. The model examines the effects of feature and technology level, as well as advertisement on vehicle pricing. To examine the proposed approach and model, several numerical examples are applied. The results reveal that the model can increase the manufacturer's profit by considering the government benefits, as well as the retailer’s profit. Finally, some managerial implications are developed by a sensitivity analysis of the main parameters.

In this paper, the optimal interest rate on bank deposits is calculated according to monetary policy in the Iranian banking system. The interest rate on deposits is determined using the game theory and a Stackelberg game approach. The game leader is the Central Bank of the Islamic Republic of Iran, while the followers include three banks called A, B, and C. The leader of the game regulates its monetary policies in the form of three scenarios and the variables of "legal deposit award rate", "legal deposit ratio", and "rate of bank commission received" from the followers (the banking system). The follower players also determine the "interest rate on deposits" based on the strategy of the leader player. The overall results of this study indicated that in this Stackelberg game, the optimal scenario of the central bank involves "reducing the rate of commissions received" from the banking system and "increasing the legal deposit award rate" under conditions where the coefficient of the importance of the components of the utility function (social welfare) of this bank and the coefficient for facilities paid by this bank to the government, companies, banks, and governmental institutes are complete ( equalling to one), and that the scenario of changing the percentage (ratio) of the legal deposit is not optimal. Meanwhile, the optimal scenario of the follower players was reducing the interest rate on deposits in 2016. Also, the players of this game will be more profitable than their current situation if they choose Stackelberg's game.

The destructive effects of corporate earnings manipulation and the contradictory empirical evidence surrounding the effect of CEO's psychological characteristics on the likelihood of earnings manipulation have doubled need to explain the reasons for this relationship.Given that the decision to manipulate profits is with the management of the company, so his psychological characteristics can be effective in whether or not to manipulate profits. The purpose of this study is to investigate the effect of narcissistic and overconfidence characteristics of the CEO on the possibility of profit manipulation using the Benish model and to analyze the auditor's reaction to the possibility of profit manipulation.

The present research is applied in terms of purpose and the research method is post-event causal. To test the research hypotheses, 156 companies have been selected from the companies listed on the Tehran Stock Exchange in the period 2012-2018.

The results of the research using binary logistic regression indicate the effect of CEO narcissism on the possibility of profit manipulation using the modified Banish model. Also, other research hypotheses about the relationship between CEO overconfidence and the possibility of profit manipulation as well as the auditor's reaction to the possibility of profit manipulation were not confirmed.

This paper studies the monetary policies of the central bank to determine the inter-est rate on deposits in the interaction with the Iranian banking system in the form of Stackelberg and Nash equilibrium games. The leader of the game is the central bank of the Islamic Republic of Iran, while the followers of the game include three banks called A, B, and C. The leader of the game regulates its monetary policies based on the relationship between inflation rate and interest rate on depos-its in the form of three scenarios of "legal deposit ratio", "legal deposit award rate", and "the rate of commissions received" from the followers. The follower players also determine "the interest rate on deposits," based on the scenarios of the leader player. The results of this research (2010-2019) by MINITAB Soft-ware indicated that in the studied year (2019), the strategy of the players of this game has been mostly Nash (more competitive) rather than cooperative. If the players of this game had chosen cooperative strategy (Stackelberg game), they would have achieved greater profit. Also, the optimal tool for the monetary policy of the leader and follower players has been the “increasing the legal reserve re-ward rate".

This study seeks to introduce the influential factors in controlling and dealing with uncertainty in intermittent demand. Hybrid forecasting and Grey Theory, due to their potential in facing complex nature, insufficient data, have been used simultaneously. Different modeling, unbiased weighting results have been used in estimating the safety stock(SS) by both theoretical and experimental methods. In other words, this work deals with the less studied feature of various modeling errors and their effect on SS determination and recommends its use to address the uncertainty of intermittent demand as a criterion for introducing a superior model in the field of inventory.

The present study is presented in order to determine the optimal investment portfolios between a bank and its customers, in the form of a two-level game by Stackelberg (leader-follower). The game is based on the Markowitz mean-variance model. Leader player portfolios (Bank 3) have included deposit portfolios in rival banks (Banks 1 and 2), investment in the real estate market, investment in the stock market and investment in the foreign exchange market. Also follower player portfolios (Bank 3 customers), including deposits in rival Banks(1,2), investment in the coin and gold market, investment in the foreign exchange market, investment in the housing and real estate market, investment in the car market, investment in the stock market. The data related to the mentioned assets covered 2009-2017, where the optimal investment portfolios of the players was first determined using GAMS software. Next, the problem was solved again using the meta-heuristic algorithm of Firefly in Matlab Software. Eventually, the optimal technique was chosen. Finally, the results of the study showed that the optimal investment portfolios for the leader player include investing in the real estate market and investing in the stock market, respectively. Also, the optimal investment portfolios of the following player include depositing in Bank 2, investing in the coin and gold market, investing in the stock market and investing in the real estate market, respectively.

The construction industry and the implementation of civil engineering projects are considered as one of the causes of environmental pollution. Considering the destructive effects and the contaminants created by the implementation of the development plans, it is necessary to evaluate the environmental impacts and identify them in order to reduce the impacts. The purpose of this study was to evaluate the environmental impacts of the rural water supply project in Birjand city using the Leopold Matrix Method of Iran.

In this study, the environmental impacts of rural water supply project implementation in Birjand city during the year 2019 and in two physical-chemical and biological environments and in the construction phase were evaluated using Iranian matrix method. To this end, various implementation modes have been formulated to evaluate the environmental impacts of the project activities and a Leopold Matrix has been developed for each of them.

The results showed that the average environmental impacts during construction in the 7 execution modes were -1.58, -1.95, -2.15, -2.5, -2, -2.21 and -2.22. Also, the number of environmental impacts on surface and groundwater pollution are highest and protected areas are least.

According to the analysis performed in none of the seven matrices and columns examined for the executable states, the average rankings were not found to be less than -3.1. So the project execution the supply is approved. To minimize the impacts, the lowest environmental impacts of each activity were selected, which would mean the average environmental impact of the whole project -1.52.

We always face a range of ambiguity, uncertainty and risk in variables in qualitative, non-numerical and expert-centered issues. The root of this ambiguity can be in the variable itself or other variables related to it and the statements of experts. Fuzzy cognitive mapping is one of the common models for better understanding of problems that pays attention to the cause-and-effect relationship between variables. When dealing with problems where the numerical data associated with it are not available or the nature of the problem is qualitative, perceptual mapping is made by experts. One of the problems of using the common cognitive mapping model is not considering the uncertainty, risk and error in the opinions of experts. This problem affects the quality and validity of models created in complex problems. In this paper, in order to help understand the problem correctly and eliminate uncertainty, ambiguity and risk in experts' comments on variables and cause-and-effect relationships between them, the combined approach of Z-number and R-number in fuzzy cognitive mapping has been used. The proposed method in this article, by considering optimistic, pessimistic and neutral experts, has modeled the cause-and-effect relationships between strategies affecting the empowerment of individuals in the health system. The proposed approach of this research can be effective as a decision support method in issues that are qualitative and expert in nature.

Proper performance of production/supply centers in a multi-factory production (MFP) network requires undisrupted equipment. The design and implementation of a maintenance system is important for two reasons - firstly, extending the life of the equipment, and second, reducing the MFP network disruption and associated costs. The greater productivity of an MFP system is achieved by integrating maintenance and production decisions. In this study, considering a scenario-based uncertainty in the demand and failure rate, a robust scenario-based stochastic programming (RSSP) model has been presented. proposed RSSP model integrates the strategic and operational decisions of production and the maintenance, and takes into account the MFP disruption costs. We suggest three preventive maintenance strategies such as maintenance outsourcing, deployment of backup equipment, as well as periodic preventive maintenance for the MFP network. The objective function of the proposed model is to maximize the total profit, subject to, constraints such as limited capacity of production, storage, access to service centers, and budget should be satisfied. The proposed RSSP model is formulated as mixed linear program which can be solved in small-scale instances by the CPLEX Solver. Furthermore, Benders decomposition solution method is proposed for large-scale instances. Finally, a numerical study of CNG stations, as an MFP network, is conduct to demonstrate the applicability of the proposed model and analyze the results.

Usually, in real-world engineering problems, there are different types of uncertainties about the studied variables, which can be due to the specific variables under investigation or interaction between them. Fuzzy cognitive maps, which addresses the cause-effect relation between variables, is one of the most common models for better understanding of the problems, especially when the quantitative data are not available or the nature of the problem is qualitative. One of the significant issues of automatic construction of fuzzy cognitive maps is that it does not consider the experts' uncertainties because of their cognitive attitudes such as age, experience, etc., which affects the quality and validity of modeling of the complex problems. Therefore, in this paper, a Z-Cognitive maps approach is proposed based on the distance-based automatic construction approach and Z-numbers to capture uncertainty and ambiguity of experts' opinions on the variables and causality relationships. The suggested approach can act as decision support for cognitive maps problems considering the experts' cognitive information, which is tested by a numerical example.

As the world's population grows and energy resources are limited, all countries face energy problems. The crises that threaten countries and communities are the lack of non-renewable sources of energy (fossil fuels), as well as the increase of environmental pollution caused by excessive consumption of fossil fuels which shows the necessities and importance of using renewable energy resources. The close link between the economic and environmental issues has raised new approaches to the field of international environmental law, one of the most prominent of which is the green economy, and since one of the main goals of the green economy is reducing greenhouse gas emissions, the use of renewable energy sources is a quick way to achieve a green economy. In this regard, the main objective of this study is to review the comparative effect of renewable energy on green economy in two groups of selected countries that produce and consume renewable energy with high and middle income.

This study is an applied research and inferential research method. The method and tool for collecting information and statistical resources are written documents, electronic information and taking notes.

The results of model estimation in the selected countries with Fixed Effects Method during the period of 2005-2016 showed that the use of renewable energy has a negative and significant effect on carbon dioxide emissions as an indicator of the green economy in the selected countries. Also, the effect of renewable energy on the green economy in the group of selected middle income countries is higher than that of high-income countries. Other results showed that economic growth and openness had a positive and significant impact, human capital, ICT and rule of law had a negative and significant impact on carbon dioxide emissions as an indicator of green economy in the group of selected countries.

Renewable energies are clean, abundant and reliable and if properly developed, can play a significant role in achieving sustainable development goals as sustainable sources of energy. The main reason for the emphasis on the use of renewable energies, in addition to helping to solve environmental problems and preventing the loss of fossil fuels, is the conservation of natural resources for future generations, which undoubtedly renewable energy, given their simplicity of technology, plays a significant role in the green economy and sustainable economic development.

Usually uncertainty and risk are the inherent characteristics of implementing large projects. This uncertainty leads to a significant failure of most of the country's projects in achieving their predetermined goals. Most of the previous studies have addressed environmental risk assessment. in this study a problem is proposed in the form of a linear integer programming optimization model to select appropriate risk responses to project risk with an environmental approach. Failure in accurately identifying the risks of construction projects, in addition to increasing the time and cost of final projects, leads to social, environmental and human damages. The aim of this study is to present a mathematical model for selecting the strategies to respond the environmental and occupational health risks according to IS0 14001-OHSAS 18001 standard of construction projects. All environmental risks of the project are detected and a solution process is proposed using a mathematical model and NSGAII metaheuristic algorithm to obtain a more favorable strategy for responding the environmental risks of a building construction project with respect to time, cost and quality. The results showed that the appropriate strategies for responding the risks were chosen optimally and the risk management system in this project was properly implemented by applying the proposed mathematical model to the 10 significant environmental risks in the project identified by the FMEA method and the ISO 31000 standard which is related to 8 important and critical activities of the project based on the failure structure. Selection of appropriate strategies for responding the risks of construction projects is one of the concerns of project stakeholders. For the first time, a metaheuristic algorithm was used to select the strategies for responding the HSE risk of construction projects. In Saba Tower, as a case study, all the risks affecting the environmental and occupational health debate were identified and appropriate risk response strategies were provided for each risk.

Estimating the cost of a project is one of the most important issues in project execution and implementation. EVM is a technique to answer this key topic. In the provided relationships for evaluating and estimating the cost of a project, project performance is assessed on the basis of previous data and information. The purpose of this study is to provide a more accurate estimate of the cost of the project at each stage. In addition to cost performance and past scheduling in this study, quality and risk factors have been investigated. Also, uncertainty in the time of the activities is considered as a variable in calculations and predictions. The results of study through an explained example shows that the addition of two factors such as risk and quality predict 40 percent of the cost of project execution and predicting the future performance of the project and provide more accurate information to the managers and stakeholders for the effective implementation of the project. Also, uncertainty in predicting the duration of activities is Affected by an estimated 35% on the cost estimate

Performance appraisal is one of the key factors in optimization and improvement of organizational processes. In present dynamic environment’s Human Resources are one of the main organizations valuable assets and performance evaluations of these great assets are to enhance their future value. Therefore, selection and implementation of specific performance appraisal method is of high importance. In this research, after selecting and ranking the most accurate Performance appraisal method with multiple criteria decision making techniques such as TOPSIS, Multi-MOORA and Entropy-weighted multi-MOORA methods, a comparison and analysis between Performance appraisal methods discussed. In order to select a specific method of performance appraisal, Characteristics and criterion of each method analyzed in the current literature review. A comparison between modern MCDM methods such as Multi-MOORA and traditional MCDM methods like TOPSIS and SAW takes place by analyzing the correlation between methods with Spearman's rank correlation coefficient. Subsequently, in current research by adopting MCDM methods ranking of popular performance appraisal due to the library research computed. Comparing traditional methods (i.e. TOPSIS and SAW) with Modern method such as multi-MOORA shows high correlation of approaches.

In this paper, a fuzzy multi-objective model is presented to select and allocate the order to the suppliers in uncertainty conditions, considering multi-period, multi-source, and multi-product cases at two levels of a supply chain with pricing considerations. Objective functions considered in this study as the measures to evaluate the suppliers are the purchase, transportation, and ordering costs, timely delivering or deference shipment quality or wastages which are amongst major quality aspects. Partial and general coverage of suppliers in respect of distance and finally supplier's weights make the amounts of products orders more realistic. Deference and coverage parameters in the model are considered as uncertain and random triangular fuzzy number. Since the proposed mathematical model is NP-hard, multi-objective particle swarm optimization (MOPSO) algorithm is presented. To validate the performance of MOPSO, we applied non-dominated sorting genetic algorithm (NSGA-II). Taguchi technique is executed to tune the parameters of both algorithms. A practical case study in an agricultural industry is shown to demonstrate that the proposed algorithm applies to the real-world problems. The results are analyzed using quantitative criteria, performing parametric, and non-parametric statistical analysis.

Tax fraud essentially entails cheating on a tax return in an attempt to avoid paying the entire tax obligation. Tax fraud is one of the most important issues in each economic system which can be difficultly analyzed. The aim of this research paper is to identify the causal relationships and prioritize the main effective factors in tax fraud in Iran. In this paper, we use Decision Making Trial and Evaluation (DEMATEL) technique together with Group Analytic Network Process (ANP) method in fuzzy environment. Also, we propose an experimental example to show that the fuzzy Multi Criteria Decision Making (MCDM) model can measure and evaluate the tax fraud issue in real world problems. The findings and results can be presented to the decision makers to select the best solution in order to prevent and confront the tax fraud problem. Finally, five principal factors and twenty secondary factors in tax fraud problem are identified and analyzed by the proposed model and interviewing with experts.

As a result of the privatization and transfer of management and ownership of public companies to the private sector, it was expected that the efficiency of these companies will increase. This paper considers evaluating the effects of privatization of 52 of 195 companies affiliated to public parent organization. In this paper, we present a conceptual and operational model to evaluate relative efficiency of the companies transferred to the private sector in the years before and after the assignment. Then, the model is used to calculate relative efficiency of 52 companies.
Model used, which uses data envelopment analysis is a nonparametric approach to determine the relative efficiency of decision making units, and has various inputs and outputs.
By using this method, we found that the relative efficiency of 7 of the 52 companies studied reduced compared to pre-assignment period and relative efficiency of other 45 units has improved. This result shows that the privatization process has been successful in industrial companies under study. In order to survey the privatization impact on the efficiency of economic units, the mean equality test two sample hypothesis testing methods were used. Based on to data, at 95 percent confidence interval, it can be said that the privatization processes in industrial plants studied, has been successful.

Scheduling problems play a big role in manufacturing and planning the production for increasing the production efficiency and assigning the resources to operations. Furthermore, in many manufacturing systems there is a physical space between stages that called intermediate buffers. In this study, a model is proposed for minimizing the makespan of a hybrid flow shop scheduling problem with intermediate buffers and resource constraints. These constraints exist in almost every realistic manufacturing system and have an imperative impact on improving the production cost, productivity, and sustainability. In this study, a hybrid algorithm based on genetic algorithm and variable neighborhood search was used, which in tuned with Taguchi’s method helped in solving the proposed model for a tire manufacturing company. The results show that the proposed mathematical model has a high ability for scheduling problems with resource and intermediate buffer constraints and is solvable by the hybrid genetic algorithm.

Nowadays competitive markets and development of managerial concepts force companies to better design and manage their supply chains. Supply chain management emphasizes on integration of supply chain Components. It is not possible to individually consider supply chain Components’ decisions for improving the supply chain performance. Since the key role of location-routing factor is obvious, the integration of these Components results in an efficient and effective supply chain. This research studies the design of perishable food supply chain with the risk of disorder which includes facility location, assign of flows between facilities, and routing decisions. In this research, the perishable food is distributed from the suppliers to the distribution centers and from the distribution centers to the demand centers. The aim of this study is to present a fuzzy model for locating distribution centers and routing vehicles from suppliers to demand centers. The presented model is solved by LP-metric method and GAMS software. The results of this research reveal that increasing costs decreases shortage and vice versa. Also, cost increase yields more cover percentage and all zones can be covered by maximum costs.

This paper propose a solution method for assigning limited liquidity to contractors based on the project priorities which is one of the current issues in project liquidity management. The aim of this research is to introduce an approach to resolve the problems of public contractors in assigning resources to oil and gas projects. In this paper, first the effecting indices on contractor's performance are determined by Fuzzy AHP method. Then, the importance weights of the related criteria are calculated and the final scores of the contractors are found by TOPSIS technique based on the indices. Afterwards, the contractors are ranked. At the end, the method of assigning limited liquidity to the contractors is introduced using a heuristic algorithm. The actual data of a public contractor in oil and gas industry are used to illustrate the proposed procedure. Finally, the results and suggestions for further improvement are shown.