supply chain management analyzing/modelling
Javad Mohammadghasemi; esmaeil najafi; mohammad fallah; mohammad reza nabatchian
Abstract
In this paper, the modeling of a sustainable supply chain network of the electricity industry under uncertainty is discussed. The purpose of providing this supply chain network is to meet the customers' demand for solar panels in order to produce clean energy. In this model, important decisions were ...
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In this paper, the modeling of a sustainable supply chain network of the electricity industry under uncertainty is discussed. The purpose of providing this supply chain network is to meet the customers' demand for solar panels in order to produce clean energy. In this model, important decisions were made, including supplier selection, construction of production centers, optimal allocation of product flow and solar panel pricing. The results of the model showed that with increasing reliability in the network, the amount of net present value in the network has decreased and the amount of greenhouse gas emissions in the network has increased. Also, the analysis of the results showed that with the increase in the uncertainty rate in the network, the net present value and reliability in the network decreased and the amount of greenhouse gas emissions increased. On the other hand, further analysis on 15 numerical examples showed the high efficiency of two algorithms, MOALO and MOWOA, compared to the epsilon constraint method. Finally, the results of the statistical test also showed that there was no significant difference between the averages of the number of effective answers, the maximum spread and the metric distance between the two algorithms, and there was only a significant difference between the solving time of the two algorithms. The results of the presented solution methods show their high efficiency in solving the sustainable supply chain network model of the electricity industry.
Fuzzy Optimization
Mehrdad Rasoulzadeh; Seyyed Ahmad Edalatpanah; mohammad fallah; esmaeil najafi
Abstract
Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking ...
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Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking to reduce risk at a certain level of Returns are expected. For this purpose, investors mainly use the concepts of fundamental analysis and paying attention to the internal structure and financial performance of companies, or paying attention to the changes and price fluctuations of stocks in the market, or a combination of both methods.Research methodology: In this research, by combining the Markowitz model with fuzzy returns with the network data coverage analysis model, we will achieve a multi-objective model, which by considering the performance of companies based on some financial ratios and its effect on the stock market value, Also, price fluctuations will try to introduce stock portfolios in the best possible situations in terms of risk, return and efficiency of the stock portfolio. Finally, in order to use the model in selecting an optimal portfolio, 50 companies were selected from the active companies in the Tehran Stock Exchange, and the said model was implemented on them. Also, multi-objective algorithm with non-dominated sorting was used to solve the model.Findings: The results obtained from the implementation of the model on 50 companies active in the stock exchange show that the use of the proposed model is better than the use of any of Markobetz's models or network data coverage analysis alone, and also the ratio The non-network model provides investors with better results in terms of returns, risk and efficiency.
Data Envelopment Analyses
Hosseinali Heydarzadeh; Fraydoon Rahnamay Roodposhti; Alireza Rashidi Komijan; esmaeil najafi
Abstract
Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form ...
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Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form a diversified portfolio consisting of assets with varying degrees of performance.Methodology:In this study, the diversified portfolio's performance based on the risk-adjusted value and conditional risk-adjusted value obtained from the probability distributions of returns was compared with the minimum-variance Markowitz portfolio performance in terms of the Sharpe ratio. After estimating the maximum likelihood parameters of the model, the risk values for each stock were calculated based on the empirical return distribution, the Cauchy distribution, and the normal distribution. These risk values were then used in the data envelopment analysis to calculate the efficiency scores of each company.Findings:The diversified portfolio with stock performance degrees outperforms the minimum-variance Markowitz portfolio in terms of risk-adjusted and conditional risk-adjusted values. The probability distribution of returns leads to different results in calculating stock risk-adjusted value/conditional value, with the empirical return distribution and normal distribution providing a more desirable performance (in terms of the Sharpe ratio) compared to the Cauchy distribution and sample ratios.Originality/Value:In the literature, an efficient portfolio is usually formed by calculating asset weights in the stock basket so that the Sharpe ratio reaches its maximum value. In the current study, this hypothesis is challenged in favor of the proposed method, which estimates portfolio weights based on the efficiency of risky assets.
simulation techniques and expert systems
Seyedeh Raahil Mousavi; Mohammad Mehdi Sepehri; Esmaeil Najafi
Abstract
Purpose: High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this ...
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Purpose: High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this end, we seek ways of accelerating the patient flow in order to save time and cost in healthcare facilities.Methodology: In this study, we use agent-based simulation to simulate patient care in the operating room. After performing the required validations, a number of improvement scenarios were developed and evaluated.Findings: A hybrid scenario including modifications to the referral time of the patient by the surgeon, transfer time of the surgical set and supplies to the operating room, and the timing of anesthesia proved to have the most positive impact on the criteria i.e. activities, reducing the average Length of Stay (LOS) by 9.69 minutes. The second-most effective scenario involved modifying the referral time of the patient by the surgeon, reduced the LOS by 7.31 minutes.Originality/Value: Through this research, it became apparent that minimizing the patients' LOS improves the efficiency of the operating room as it helps reduce the overall idle time and increases the number of operations carried out in each shift. Making time even for one additional operation per day significantly increases the operating room income. Moreover, a shorter LOS means less fatigue for the medical staff and reduces the total cost of running the operating room by reducing the staff's overtime hours.
Combinatorial Optimization
Mohammad Jaberi; Seyyed Esmaeil Najafi; Farhad Hoseinzadeh Lotfi; Mohammad Haji molana
Abstract
Purpose: Strategy is the main source of long-term growth of organizations and if the strategy is not successfully implemented, even if the appropriate strategies are adopted, this process is useless. The purpose of this paper is to propose a comprehensive hybrid model for predicting organizational performance ...
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Purpose: Strategy is the main source of long-term growth of organizations and if the strategy is not successfully implemented, even if the appropriate strategies are adopted, this process is useless. The purpose of this paper is to propose a comprehensive hybrid model for predicting organizational performance indicators.Methodology: In order to achieve the research goal, first, a balanced scorecard as a tool for designing performance evaluation indicators and network data envelopment analysis as a tool for performance evaluation has been used. Then, by matching the Malmquist productivity index with the mentioned hybrid model, the model of progress and regression of organizations in two consecutive periods is presented. Finally, by combining the proposed models and artificial neural networks, a solution is presented to evaluate the performance of 500 bank branches and also to identify their progress and regression.Finding: The obtained results show good accuracy and less computational time of the proposed hybrid models.</pOriginality/Value: The present study can add to the existing knowledge on performance appraisal of enterprises by providing a hybrid model using network data envelopment analysis and balanced scorecard; And the proposed methods can be promising tools for evaluating the performance of organizations, especially big data.
Multi-Attribute Decision Making
Mojtaba Akbarian; Esmaeel Najafi
Abstract
The strategy is most resources for organizational long term improvement and if it don’t deployment successfully, this process is ineffective even if appropriate strategies are released. The most stage in strategic deployment is resource allocation for implementation of strategic initiatives. With ...
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The strategy is most resources for organizational long term improvement and if it don’t deployment successfully, this process is ineffective even if appropriate strategies are released. The most stage in strategic deployment is resource allocation for implementation of strategic initiatives. With regard to resource restriction in the deployment of strategy, the ranking of strategic objectives with cause and effect relationships in the strategy map is important . In this paper after drawing of strategy map with DEMATEL method and identifying cause and effect relations between strategic objectives as network relations, the weight of each criterion is defined with analytic network process, and strategic objectives in the National Iranian Oil Refining & Distribution Company are ranked and according to this ranking strategic initiative are assigned.
Data Envelopment Analyses
Hadis Drikvand; seyed esmaeel najafi
Abstract
Data envelopment analysis measures relative efficiency of DMUs with multiple inputs and outputs, the importance of identifying efficient and inefficient DMUs and organizing inefficient DMUs have led to paying more attention to key role of data envelopment analysis, Input and output data are not always ...
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Data envelopment analysis measures relative efficiency of DMUs with multiple inputs and outputs, the importance of identifying efficient and inefficient DMUs and organizing inefficient DMUs have led to paying more attention to key role of data envelopment analysis, Input and output data are not always desirable and there exist a number of undesirable data which affect the efficiency. In addition, uncertainty is undeniable feature of the real world. For this purpose, in this paper, it is attempted to approach the reality by considering undesirable and fuzzy data simultaneously. Traditional DEA divides DMUs into efficient and inefficient, it is not able to rank DMUs completely, therefore, optimistic cross efficiency method is utilized to face with this defect and then the proposed multi-objective model is solved as a single-objective one applying Torabi-Hassini method. Finally, to demonstrate the efficiency and effectiveness of the model, a numerical example is used and the findings are compered.