hamed rafiei

The industrialization of communities has led to an increase in greenhouse gases over recent decades. This increase has caused the warming of the earth's atmosphere, and it affected other components of the climate system and led to climate change. The evidence confirms that the global average temperature of the Earth is increasing, especially in recent years. Moreover, precipitation intensity has changed over time. It is expected that changes in temperature and precipitation will cause a series of climatic extreme events. Therefore, it is an undeniable fact that the intensification of global climate change has affected the development and survival of mankind. The purpose of this research is to investigate and predict these changes in the future decades in the Taleqan watershed, Iran.

The study area, Taleqan watershed with a mountainous topography, is located in the northwest of Alborz province, Iran. The annual precipitation and temperature of the region are 485.8mm and 11.4℃, respectively. To estimate and generate data for the future period (2021-2040), we used daily data from regional stations, including precipitation data from the base period (1979-2014) and average temperature data from the base period (2003-2014). We also utilized output data from the General Circulation Model (CanESM5) under climate scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). CanESM5 is a global model developed for simulating future climate change and developing seasonal and decadal forecasts. CanESM5 is usually used for large-scale projections, therefore, SDSM is chosen to downscale climate data. The changes of average precipitation and temperature parameters for three future periods (2021-2040, 2041-2060, and 2081-2100) were evaluated and RMSE, MAD and R were used to evaluate model accuracy.

The greatest increase in precipitation in Armot station is in March, May and November and the greatest decrease in precipitation in September and October is predicted under the SSP scenarios for the periods 2021-2040, 2041-2060 and 2081-2100. In Sakranchal station, the highest increase in precipitation is in three periods of March, February and May, and the highest decrease is in September and October under the SSP1-2.6, SSP2-4.5 and SSP5-8.5. The highest increase in precipitation in the Zidasht station is in March, May and November, April and December under the SSP scenarios. Also, the biggest decrease is in September under the SSP scenarios for the three forecast periods. In Gateh Deh station, the highest increase in precipitation during the periods of 2021-2040 and 2081-2100 is related to March, May and November, and for the period of 2041-2060, it is related to the months of March, February and May under the SSP5-8.5. During the periods of 2021-2040 and 2041-2060, the greatest decrease will be in September under the SSP scenarios, also in the period of 2081-2100, the greatest decrease will be in July under the SSP scenarios and in October, under the SSP5-8.5. During three periods, the greatest increase in Jovestan station precipitation is predicted in February, March, May and November. Also, the greatest decrease in the period of 2021-2040 will be in September and August under the SSP5-8.5 and in the periods of 2041-2060 and 2081-2100 in October and July under the SSP1-2.6. Based on the results of the temperature forecast in Zidasht station during three periods, the average and average maximum temperature in January and February under the SSP scenarios have a decreasing trend and other months show an increasing trend.

The results show that precipitation has a decreasing trend in some months and some increasing trend. The obtained results indicate that the precipitation and temperature variables in the periods of the 2021-2040, 2041-2060 and 2081-2100 under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 will experience an increasing trend compared to the base period. The highest increase in temperature and precipitation is in the period of 2021-2040 under scenarios SSP2-4.5 and SSP1-2.6, respectively. This study demonstrates that Taleqan watershed will be vulnerable to future climate change. An increase in temperature can cause snowmelt and reduce snow storage. The stability time of water reserves in the watershed will be reduced. Precipitation changes in the region can alter the precipitation pattern from snow to rain. This reduces surface and underground water, and can affect crop yield.

In today's world, we are faced with a huge amount of growing information and uncertainty. Uncertainty in information has different types of ambiguity, possibility, probability, inaccuracy, etc., which make the use of information a challenge. Fuzzy logic, as a solution to deal with uncertainty, only deals with a certain part of these uncertainties and does not consider other aspects. In 2011, Zadeh proposed the concept of Z numbers, which consist of two components, the limit and the reliability of the limit, to cover possible and probable uncertainties.In this review article, the study of the background of Z numbers and its mathematical foundations will be discussed first. Then, the most important researches conducted in the applied fields of Z numbers include decision making, ranking, word calculations, machine learning, medical diagnosis, risk assessment, regression analysis, and review control. Examining the results of the articles indicates that the use of Z numbers can significantly improve the amount of error and accuracy. But the complexity of the calculations and the learning process in these structures are among the upcoming challenges in this field. Also, the use of Z numbers in some areas such as forecasting and optimization is among the future horizons.​

Low income level of local communities is one of the causes of natural land degradation. Implementation of moringa peregrina cultivation development plan in the desert areas of southern Iran leads to its economic development. The economic level required by every rural household has become. The research data were extracted from the moringa peregrina development plan prepared by the Forests, Rangelands and Watershed Management Organization and all data were calculated in the base year of 1400. Due to the limited land and the need for an appropriate criterion for the participation of each rural household, the minimum economic level was determined in each of the executive areas. Determining the minimum economic level using the financial evaluation of the project, financial indicators of net present value (NPV), Benefit Cost Ratio (BCR), internal rate of return (IRR) and return on investment (ROI) for the duration of the project from 1400 to 1420 Was examined. Considering the location and topography of the region in general, financial indicators indicate the appropriateness and profitability of the project. Taking into account the average costs of each household in the village of Sistan and Baluchestan province in the implementation of the plan of minimum economic level in plain areas (0.8 hectares), flat areas (3.24 hectares), terrace areas (4.48 hectares), areas Mahour hill (11.08 hectares) and mountainous and impassable areas (6.21 hectares) have been estimated. The minimum level obtained can provide decision makers with valuable information for desert land management in areas prone to moringa peregrina cultivation.

The aim of this study is to determine the optimal tariff for treated wastewater in the agricultural sector in the south of Tehran province. In order to achieve this goal, Used of positive mathematical programming (PMP) optimization method and the conditional valuation method (CVM) to estimate the conservation value. The required information was collected by completing 470 questionnaires by two-stage cluster sampling in the south of Tehran province in 2019. Based on the results, the cost price of treated wastewater was determined to be 21,523 Rial per cubic meter in Tehran province. Market price for each cubic meter of treated wastewater in Qarchak, Pishva, Rey and Varamin cities is 4444, 5556, 9778 and 5000 Rial respectively, value Marginal production is 10080, 15720, 17090 and 12370 Rial and willingness to pay of farmer 9474, 10136, 10173 and was determined to be 10671 Rial. Finally, by examining the conditions of market formation, the optimal tariff for treated wastewater in the south of Tehran province (PEWW) was determined to be 10,114 Rial per cubic meter. Due to the high cost price of each cubic meter of treated farmers are, it is suggested that the private sector enter the wastewater treatment market, because it can pay the difference between the cost price and the willingness to pay of farmers for the treated wastewater from government environmental assistance.

the purpose of this study is investigation of the factors affecting price volatility for Iran's date. In order to investigate the factors affecting price volatility export of Iran's date has been used approach (ARDL) for 1949-2014. Among all of the variables, years of sanction and number of main target countries are significant at level of 5 percent and share of main target country is significant at the level of 10 percent. With increasing one percent in the number of main target countries, Iran's export prices will be increased in about 0.742 percent. Variable of share in main target country has negative effect on Iran's export prices. Diversity of Iran's export markets with reducing reliance of Iran's export to the main target country and more uniform distribution of export share among other target countries, creates the fewer price volatility of Iran's date export. So paying attention to the diversification of the target markets of date export with the aim of reducing Iran's price volatility in world markets will be necessary.

Traditional markets of bony fishes, the low proportion of fishermen from fishing and against, unfavorable market conditions and the high price in fish markets are major problem in Mazandaran Province’s fish market. In this market, consumer dissatisfaction and fishermen simultaneously, has created major problem for policymakers. According to consumer interests and the elimination of waste intermediate will be one of the most important factors to improve performance and market share, producer (fisherman). Designing coastal markets and selling fish caught, In addition to providing fresh fish and healthier for the consumer, will create more satisfactory to the attractiveness of these coastal markets. On this basis, this study explores the feasibility of the coastal market in types of bony fish in the province in 2012. For this purpose, 684 questionnaires to a two-stage cluster sampling between coastal and non-coastal provinces were collected. The results of the Logit model analysis indicated that in the coastal market of white fish, mullet and carp, At best; consumers are willing to pay the 16.418, 16.657 and 13.197% more than average prices. Also at worst; they are willing to pay the 7.634, 6.280 and 5.243% more than average prices. In non-coastal markets also showed that in best, consumers are willing to pay for the coastal market, 14.302, 12.590 and 11.185% and at worse they are willing to pay 5.243, 6.02 and 3.995% more than average prices. Therefore designing the coastal market according to reduce transaction cost to wholesale and retail market and for increasing fisherman’s market share will be necessary.

The aim of this study is to assess the potential of beekeeping and determination of attractiveness range plants used bee by geographic information system (GIS) in 2015 in Char-Bagh summer rangeland, Golestan. Accordingly, the final model of beekeeping potential of combining the four main criteria of nectar and pollen composition of plants (20 points), distance from water sources (10 points), roads and access routes (10 points) and the average temperature during the course of beekeeping (10 points) was determined. After the vegetation type’s floristic-physiognomic method, sampling the vegetation types in the area delimitation random-systematic method to deploy 3 transects 300 m and 30 plots were made according to the type of vegetation. Water resources map as well as the road map was drawn using Global position system (GPS), field visit and geographic information system (GIS). Nectar and pollen 134 plant species from 80 genera and 31 plant families’ favorite bee detected. Family Asteraceae, Lamiaceae and Fabaceae, respectively, with 29 (21.8%), 23 (29.17%) and 19 (14.28%) species with the highest frequency nectar and pollen plants in the region. The results showed that plants attractive class II and III, the most appearances (60.9%) and class V least of (2.3%) in the region and with regard to regular visits on the field and during the flowering period May to August are the most plants in Char-Bagh summer rangelands. The results show that using the GIS module beekeeping potential of the pasture area 17.62% (1562.4 hectares) average potential in the floor (S2), 72.41% (6419.76 hectares) on the low potential (S3) and 9.96% (883.5 ha) in the class of potential (N) is located. According to the results area of about 90.03% (7982.17 hectares) has been potential the principles of apiculture, beekeeping can be attempted with the principles and also earn money by reducing grazing pasture helped to revive.

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

This paper addresses a new product positioning problem, in which prices of the products are simultaneously determined in order to maximize both customer satisfaction and seller’s net profit. In this regard, customer willingness is identified with respect to the products within a family, upon which prices of the products are optimized so as to attain two objective functions: 1) maximizing customer satisfaction and 2) maximizing seller’s net profit. Despite of the literature body which has taken this problem into account for a single product, the developed model in this paper considers the case of a multiple products for different customer segments. To do so, an algorithm is developed which the considered problem is divided into a number of sub-problems solved by using GAMS and Matlab. Finally, a numerical example is illustrated.

Cell formation problem mainly addresses how machines should be grouped and parts be processed in cells. In dynamic environments, product mix and demand are changed in each period of the planning horizon. Incorporating such assumption in the model increases flexibility of the system to meet customers’ requirements. In this model, to ensure the reliability of the system in presence of unreliable machines, alternative routing process as well as buffer storage are considered to reduce detrimental effects of machine failure. This problem is presented by a nonlinear mixed integer programming model attempting to minimize the overall cost of the system. To solve the model in large scale for practical purposes, a genetic algorithm approach is adopted as the model belongs to NP-hard class of problems. Sensitivity analysis is used to show the validity of the proposed model. Besides, numerical examples are used both, for small-sized and large-sized instances to show the efficiency of the method in finding near optimal solution.

Hybrid Make-To-Stock (MTS)/ Make-To-Order (MTO) production systems have recently attracted practitioners and academicians in the field of operations management, since these systems benefit from both stock-based and order-driven strategies. In this paper, capacity coordination dynamics of a hybrid MTS/MTO production system is addressed whose continuous production line comprises three workstations. Also, product portfolio of the considered system includes three kinds of products; pure MTS, pure MTO, and hybrid MTS/MTO. In the developed model, system performance is explored and assessed in terms of system delivery lead time. To do so, three capacity coordination rules are studies; simple average of expected demands, weighted average of expected demands, and the dynamic mechanism upon the difference between target and actual delivery lead times. Moreover, effects of demand uncertainty are taken into account.

Today competitive environment has enforced practitioners and researchers to pay great attention to issues enhancing both production and marketing competitiveness. To do so, it has been obligatory for the firms to consider production side activities while customer requirements are on the other side of competition. In this regard, hybrid make-to-stock (MTS)/make-to-order (MTO) production systems have revealed outstanding results. This paper addresses multi-site production planning of a hybrid manufacturing firm for the first time in the hybrid systems’ body of literature. In this regard, a network of suppliers, manufacturers and customers is considered for which a mixed-integer mathematical model is proposed. Objective function of the proposed mathematical model seeks to maximize profitability of the manufacturing firm. Because of computational complexity of the developed mathematical model, a genetic algorithm is developed upon which numerical experiments are reported in order to show validity and applicability of the proposed model.

In this paper, we apply continuous review (S-1, S) policy for inventory control in a three-echelon supply chain (SC) including r identical retailers, a central warehouse with limited storage space, and two independent manufacturing plants which offer two kinds of product to the customer. The warehouse of the model follows (M/M/1) queue model where customer demands follow a Poisson probability distribution function, and customer serving time is exponential random variable. To evaluate the effect of considering bi-product developed model, solution of the developed model is compared with that of the two (M/M/1) queue models which are separately developed for each product. Moreover, and in order to cope with the computational complexity of the developed model, a particle swarm optimization algorithm is adopted. Through the conducted numerical experiments, it is shown that total profit of the SC is significantly enhanced using the developed model.

One of the main factors affecting on the technical and economic performance of farms and livestock is the ability or capacity management. Main goal of farm management is achieving specific performance, profitability and productivity; there for measurement management and performance in livestock farms are necessary. Considering the necessity of increasing production and quality in the dairy industry, to investigate the effect of different inputs and also total factor productivity and management impact on output and profitability, milk production and profit functions, were estimated using Ordinary Least Squares (OLS) method. In this study, data and information were collected by studying documents, observation and interview procedures. Results of production and profit functions estimation showed that productivity and management have positive significant effects on output and profitability. The total factor productivity of them was measured using Tornqvist-Theil indicator; total factor productivity of farms was calculated 0.92 in average. Also, management index for each farm were measured using Multiple Attribute Decision Making (MADM) techniques; the average of management indicator were obtained 0.55. Among the variables included in the production function, two edible inputs; concentrates and alfalfa, and then the labor, respectively have the highest milk production elasticity. It was also showed that the fuel input was used consumedly and in non-economic region of production. Results of profit function estimation showed that fuel price after the price of alfalfa have the greatest negative impact on profitability of dairy farms; on the other hand, concentrates price, wages and cost of each time artificial insemination, have the positive effect on profitability.