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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Industrial Strategic Management
- نوع مقاله: Journal Article
- کلمات کلیدی: * Indifference Points,* Marginal Rate of Substitution,* Metaheuristic Algorithms,* Parallel Matrixes
- چکیده:
- چکیده انگلیسی: Evaluating and selecting the right contractors can increase the chances of success of a project and the organization. Considering the intense competition faced by organizations today, proper cost management to enhance profitability and customer satisfaction has attracted a lot of attention. The evaluation of contractors is usually a process thatis based on various criteria.By the end of it, theappropriate options are selected. Given the diversity in the criteria and among thedecision-making subjects, no singleway has been offered to suggest substitution between criteria.The desirability indifference on the curve ofconsumption of various goods (selection ofdecision-making options) are the same. This paper seeks to identify parallel matrices with the initial decision-making matrix of contractors that have the same results and desirability for decision-makers (indifference points). At first, the initial rating using the AHP and TOPSIS methods andthe particle swarm optimization (PSO) and genetic algorithm (GA)techniques, along withMATLAB software,was used to identify theparallel matrices. According to the obtained results, sixparallel matrixes with the initial decision-making matrix that had been prepared by experts fromthe company were produced.Out of them, the matrix related to The point of indifference is the fifth output5 AHP-PSO, based on the company experts' opinions was selected as the final version.
- انتشار مقاله: 22-11-1396
- نویسندگان: Arshad Farahmandian,Reza Radfar,Mohammad Ali Afshar Kazemi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial Strategic Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Neural network,DEA,clustering,strategy,Energy
- چکیده:
- چکیده انگلیسی: Today, information networks play an important role in supply chain management. Therefore, in this article, clustering-based routing protocols, which are one of the most important ways to reduce energy consumption in wireless sensor networks, are used to optimize the supply chain informational cloud network. Accordingly, first, a clustering protocol is presented using self-organizing map neural network, SOM. Second, we cluster the network nodes based on two criteria of neighborhood and energy level using K-means clustering pattern. Third, we survey the efficiency and inefficiency of the clusters to balance the energy properly among the clusters. Then, to increase the network lifetime and to maintain the network DEA method is used. Finally, the model is tested for the information network of oil supply chain.
- انتشار مقاله: 27-04-1396
- نویسندگان: Mohammad Ali Afshar Kazemi,Mohammad Hossein Darvish Motevally,Mahmood Darvish Motevalli
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Information, Security and Systems Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Knowledge,knowledge management,feasibility,Effective factors in knowledge management,Knowledge management models
- چکیده:
- چکیده انگلیسی: In order to investigate and consider the feasibility of the establishment of knowledge management at Payam nour universities of Golestan province elicited from reviewing the research literature, the researchers endeavored to identify the factors affecting the establishment of knowledge management and the knowledge management components, and then to consider the way of their influence as well as their priorities. Finally, through the presented model, the best option among possible solutions is selected. The investigators have gone through the stages following positing hypotheses 1 to 5. In the end, the results of conducted research are discussed. The method of the research is descriptive-survey. Data and information is collected through the questionnaire. The statistical community of the study is faculty members and the employees (official, contractual, conditional) of all different branches of payam Nour universities in Golestan province in 89- 9o academic year. The statistical community comprises 172 people from those 76 people are chosen based on stratified sampling method. The obtained data is analyzed through inferential and mathematical statistic. Finally, a model applicable to the establishment of knowledge management at Payam Nour universities of Golestan province is presented.
- انتشار مقاله: 06-01-1391
- نویسندگان: Mohammad Reza Motadel,Mohammad Ali Afshar Kazemi,Fatemeh Goodarzi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Finance and Managerial Accounting
- نوع مقاله: Journal Article
- کلمات کلیدی: Efficiency,Benchmarking,GANN-DEA,PSOGA,Tobit regression
- چکیده:
- چکیده انگلیسی: The purpose of this study is designing a model based on Tobit regression, DEA, Artificial Neural Network, Genetic Algorithm and Particle Swarm Optimization to evaluate the efficiency and also benchmarking the efficient and inefficient units. This model has three stages, and it uses the data envelopment analysis combined model with neural network, optimized by genetic algorithm, to evaluate the relative efficiency of 16 regional electric companies of Tavanir. A two-staged approach of data envelopment analysis and Tobit regression has been used to measure the effects of environmental variables on the mean efficiency of companies. Finally we use a hybrid model of particle swarm algorithm and genetic algorithm to benchmark the efficient and inefficient units. The mean efficiency of regional electric companies have increased from 0.8934 to 0.9147, during 2012 to 2017, and regional electric companies of Azarbayjan, Isfahan, Tehran, Khorasan, Semnan, Kerman, Gilan and Yazd, had the highest mean efficiency of 1, and west regional electric companies and Fars had the lowest efficiency of 0.7047 and 0.6025, respectively.
- انتشار مقاله: 08-05-1397
- نویسندگان: Mohammad Reza Mirzaei,Mohammad Ali Afshar Kazemi,Abbas Toloie Eshlaghy
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Forecasting stock price,Industry average,Optimization algorithm,Fuzzy time series,Golden Ratio algorithm
- چکیده:
- چکیده انگلیسی: The effective role of capital in every country flows through giving guidelines for capital and resources, generalizing companies and sharing development projects with public, and also adding accredited companies stock market requires appropriate decision making for shareholders and investors who are willing to buy shares based on price mechanism. Forecasting stock price has always been a challenging task, since it is affected by many economic and non-economic factors and variables; therefore, selecting the best and the most efficient forecasting model is tough and essential. Up to now applying weighted mean called weighted mean price has been used to forecast industry average price for companies in the stock market and investors were forecasting based on this method. First we have identified 10 accredited banks in TSE and 10 banks in Iran Fara Bourse. In this article, by applying one of the mathematical optimizing techniques, industry means got calculated based on optimized parameters and compared with the industry average; in this statement we strived to find another variable that could forecast with less deviation. In the following study, by calculating frequency level of deviations, average for price forecasting in banking industry during five years is examined. Finally, the research suggests that, instead of using mean of industry average, it is better to use mean average of golden number, which will lead us to more accurate results.
- انتشار مقاله: 18-09-1397
- نویسندگان: Negar Aghaeefar,Mohammad Ebrahim Mohammad Pourzarandi,Mohammad Ali Afshar Kazemi,Mehrzad Minoie
- مشاهده