جستجوی مقالات مرتبط با کلیدواژه "fuzzy multi" در نشریات گروه "اقتصاد کشاورزی"

Given that farmers try to optimize their individual utility, they generally have different goals, most of which are economic. They usually do not pay much attention to the goals of minimizing water consumption. This study attempted to investigate the addition of water minimizing goal and setting restrictions on the supply of water to the multiple objectives of farmers. It also deals with the impact of this practice on cropping patterns, water use and gross income of farmers. To achieve this, a fuzzy multi-objective programming with nonlinear membership function (hyperbolic tangent) was used. The data was collected out of questionnaires filed by 130 farmers of Chenaran (Khorasan Razavi province) using the random cluster sampling in 2012-2013 crop year. The farmers were divided into three homogenous groups, based on the cultivation area: less than 8 hectares, from 8 to 24 hectares and more than 24 hectares. Then model optimized for each of the three groups was based on the goals of profit maximization, minimization of capital and maximization of labor. Then by adding water minimization to the objectives, effects of these changes were evaluated. The results showed that by entering the water to the objectives of farmers in groups 1 and 3, water consumption was reduced. However, it did not change in Group 2. Also in all 3 groups, onions and cucumber cultivated area was decreased. In contrast, the area under wheat cultivation increased, although this would reduce the income of farmers in all 3 groups. The results also showed that with policy of restrictions on water supply in addition to changing cropping patterns and decrease in income, the total cultivated area will decrease in all 3 groups.

Today's always Production of affordable is the concern of farmers and officials. Accordingly, it appears should be in addition to cultural and politic objectives, policy makers considered, farmer's needs and goals together. In this study, was determined crop optimal Pattern the main crops of cultivated in Khorasan Razavi Province Based on Comparative Advantage using the fuzzy multi-objective linear programming method. Next target is intended In addition Crops have comparative advantage, Objective such as maximum profit for the farmer.In this study, the data needed to determine the comparative advantage was prepared from Department of Commerce and FAO (Food and Agriculture Organization) website, also data needed to cropping pattern was prepared from 420 questionnaire that completed in Agriculture Organization of Khorasan Razavi in 2012.The results showed that crops irrigated lentils, kidney beans and corn Irrigated due to lack of comparative advantage were Remove from cropping patterns and crop rainfed and irrigated wheat, irrigated barley, Pnbhaby, dry barley, chickpea, rice, peas Irrigated, lentils rainfed and irrigated sunflower due to the low level of comparative advantage with minimal cultivation patterns And crops of sugar beet, tomato, water melon, Irrigated, Irrigated potatoes, Irrigated canola , Irrigated cucumber, Irrigated Onion and rainfed Watermelon has been the increase in the cultivated area compared to the existing model. Thus, the results suggest that in optimal allocation of scarce resources, especially water in crop production, in addition to considering traditional goals in cropping patterns, should considered goal of comparative advantage.

Today, to prevent the degradation of soil and water resources and reducing the economic and social losses, Agricultural sustainability and providing sustainable cropping patterns has become one of the main priorities for policy makers in the agricultural sector. Therefore, this study in the field of Introduce Suitable cropping pattern for Equalization consumption of chemical fertilizers and pesticides, balance between available resources and the climate, as well as optimal utilization of them in Mahidasht plain is located in Kermanshah province. For this purpose, 263 questionnaires were complete by two-stage cluster sampling in 2014, and using multi-objective and fuzzy multi-objective fractional programming models, sustainable cropping patterns in the framework technical constraints of production and self-sufficiency in providing forage and nutritional needs of livestock and poultry of this Plain presented in six different scenarios. According to the results, it can be stated that the proposed cropping patterns are more sustainable than the current cropping patterns of region. Therefore suggested that the policy makers with regard to overall and regional goals, prioritize the Implementation of each of the proposed cropping patterns. This requires the Codification of legal requirements, incentive and punitive policies and use of agricultural extension agents in order to move to the cropping pattern that proposed.

Regard to the importance of choosing the appropriate crop area planning, this article studied ways for choose the best method of planning. Accordingly in this paper we use seven simple linear programming models with the objective functions of maximum profit, minimum cost, maximum Labor, minimum water, minimum calories, minimum fertilizer and maximum ranking, and these models with ranking method were compared with multi objective and Fuzzy multi-objective linear programming. In this model, the limitations of land, labor, capital, water, upper and lower bound of area cultivation has been used. For this purpose, cost-production data in 2010 were used. Ranking result show that Fuzzy multi-objective method with hyperbolic membership function, with these limitations able to meet all targets better than other models. Another important parameter for comparison models is amount of water consumption in different month. Accordingly, maximum calories and Fuzzy multi-objective models use their maximum water in May (Ordibehasht) and other models use their maximum water in June (Khordad) and July (Tir). Due to the warm weather and high evapotranspiration during the months of June and July and also increased the need for household water in these hot months, Fuzzy multi-objective model is better to choice.