جستجوی مقالات مرتبط با کلیدواژه « promethee method » در نشریات گروه « فنی و مهندسی »

Cash transfer from the central treasury to the bank branches and automated teller machines (ATMs) all over the city is one of the vital processes in a banking system. There are multiple factors (e.g., location of the treasury, transportation fleet, geographic distribution of the branches and ATMs, the demand for cash, customer satisfaction, and traffic that influence the efficiency of the cash transfer). Moreover, environmental issues, and in particular the issue of greenhouse gas (GHG) emissions are given weight. In this paper, a new mathematical model for a location-routing problem with transport vehicles in the banking system is developed based on urban traffic in such a way that three objectives of decreasing greenhouse emissions, reducing location and routing costs, and increasing customer satisfaction are taken into consideration simultaneously. Furthermore, a new multi-objective genetic algorithm hybridized with a PROMETHEE method, namely the multi-objective genetic-PROMETHEE algorithm (MOGPA), is developed to tackle the proposed model. The efficiency of the proposed algorithm is examined by comparing it with the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective imperialist competitive algorithm (MOICA) for the real-case issue of Saman Bank. Because management assumptions are considered in the preference functions of the proposed algorithm, the results show that the solutions of the proposed algorithm are more efficient and closer to reality.

Estimating the costs of mine reclamation is a significant part of mine closure projects. One approach to mine reclamation is planting mine areas. In this approach, the optimum selection of plant types is cosidered a multiple-criteria decision-making (MCDM) problem. Once proper plant species are identified, it is required to estminate planting costs through statistical analysis. This work aims to introduce an algorithm for optimal plant type selection and a reclamation cost estimation model for open-pit mines. To this end, the plant species compatible with the sorrounding areas of Sungun copper mine are identified and ranked using the PROMETHEE technique. In this analysis, the main criteria are local landscape, pest resistance, plant growth ability, availability, economic issues, soil protection, water storage ability, and pollution prevention. Among the six plant types, Maple trees have the highest score (4.34). After that, to develop the reclamation cost estimation model, the data (99 datasets) is collected from the Sungun copper mine, Sarcheshmeh copper mine, and Chadormaloo iron mine. The variables in the database include soil gradation by graders, slope trimming and topography by bulldozers, the ripping and softening of the compacted soil, chemical fertilizers, natural fertilizers and mulch and biosolid, lime soil pH adjustment, herbicide, seedling, tree planting, workers and drivers, and fuel and maintenance. Regression analysis is performed to analyze the data, and a reclamation cost estimation model is developed with high accuracy (R2 = 0.78). On the whole, this study proposes an innovative, step-by-step, technical, and economic approach to the optimal selection of plant species, and presents a reclamation cost estimation model so as to promote the open-pit mine reclamation process.

All governments especially those having a high risk of natural disasters must have a comprehensive and implementable plan. In Iran, the placement of relief centers for the injured is usually done experimentally by relief organizations without considering the necessary standards. In this research, according to the crisis management standard, the criteria are classified and determined as layers of information in the Geographic Information System (GIS). Then, the selected relief centers in the study area were evaluated according to the standard criteria and using the obtained matrix, the research criteria were weighed by entropy method. Finally, using net flows, performance scores and research constraints, the optimal options were identified by the PROMETHEE 5 method. The strengths and weaknesses of each of these options were also assessed. The results showed that half of the relief centers considered in the region were not optimal and had poor performance in most of the effective and important criteria for locating relief centers. Criteria of population density and distance from worn tissue were the most important criteria in this study.

Increasing the production rate and minimizing the related costs, while optimizing the safety measures, are nowadays’ most important tasks in the mining industry. To these ends, mechanization of mines could be applied, which can result in significant cost reductions and higher levels of profitability for underground mines. The potential of a coal mine mechanization depends on some important factors such as seam inclination and thickness, geological disturbances, seam floor and roof conditions. Mechanization of underground mines requires substantial investments. Therefore, thorough inspection of pertaining aspects is of highest importance before a final decision. The main aim of this study is to develop a new approach to rank the mechanization potential of different coal seams in the Tazareh coal mine complex based on multi-criteria decision-making methods. In fact, a decision-making approach is an effective tool for dealing with complex decision-making processes, and the obtained results may aid the decision maker to determine the priorities and make the best decision. To this end, an integrated Fuzzy Delphi Analytical Hierarchy Process (FDAHP) - PROMETHEE method was utilized to rank coal stopes from the best to the worst. Among different coal seams, K19 was selected as the optimal alternative for mechanization of the Tazareh coal mine complex. In addition, in order to investigate the effects of the pertaining factors on the final decision, a sensitivity analysis was performed. The results obtained from sensitivity analysis showed that K19 with 71.4% of votes had the highest potential for mechanization.

Predicting the sawability of the dimension stone is one of the most important factors involved in production planning. Moreover, this factor can be used as an important criterion in the cost estimation and planning of the stone plants. The main purpose for carrying out this work was to rank the sawability of the dimension stone using the PROMETHEE method. In this research work, four important physical and mechanical properties of rocks including the uniaxial compressive strength, Schmiazek F-abrasivity, mohs hardness, and Young's modulus were evaluated as the criteria. During the research process, two groups of dimension stones were selected and analyzed. The rock samples were collected from a number of Iranian factories for the laboratory tests. The production rate of each sawn stone was selected to verify the proposed sawability ranking method. The results obtained showed that the new ranking method can be reliably used for evaluating the sawability of the dimension stone at any stone factory with different rocks only by the physical and mechanical properties testing.

The stock selection problem is one of the major issues in the investment industry, which is mainly solved by analyzing financial ratios. However, considering the complexity and imprecise patterns of the stock market, obvious and easy-to-understand investment rules, based on fundamental analysis, are difficult to obtain. Fundamental and technical analyses are two common methods for predicting the future behavior of the stock.Fundamental analysis focuses on the economic forces of supply and demand which cause stock prices change. On the other hand technical analysis examines historical data relating to changes in the price and trading volume by using graphs and indicators as a primary tool to predict future price movements. Therefore, in this paper, a model has been proposed for selection of the right portfolio in stock exchange. Financial industries ranking and companies ranking have been applied for selection of the right stock in this model. These rankings have been done through the PROMETHEE decision making method. Technical Analysis has been done for determining the right time to buy and sell the superior stocks. A survey has been done for determining the effective criteria over industry and company evaluation. The developed model has been applied in Tehran Stock Exchange (TSE) as a real case and a real problem has been solved. It is concluded that by using both Fundamental and Technical Analysis, an investor can get higher return on stocks instead of using just one individual analysis. In other words, while fundamental analysis distinguishes which stocks to buy, technical Analysis shows when to buy the superior stocks.Finally, some important and most commonly used indicators have been extracted. These indicators can be used by investors to consistently and correctly predict the future stocks prices.