In agricultural activities, multiple inputs and sources are use. The main objectives of farm managers and planners were to optimizing the resources usage and inputs for determining appropriate cropping pattern. Hamedan province and Bahar county has high potential for agricultural productions. The main purpose of research was to investigate optimal cropping pattern for Bahar county for crop years of 2013-2014. For the mentioned aim, mathematical planning and simulation of cropping products on the basis of water input. Data were analyzed by Lingo10 software in mathematical model. In the study, feasibility of efficiency maximization and investment cost, water usage, chemical matters minimization were analyzed according to land limitation and water availability. Results show that for the purpose of mentioned aim planning efficiency of product were increased: 8.44 percent, investment cost 2.94percent, chemical manure usage 3.05, chemical toxins usage 0.88 but water usage 1.99 percent decreased. It can be expected that findings will contribute to agricultural related organizations and planners.

In a majority of agricultural economics analyses, farmers’ economic welfare is highlighted while the environmental issues are largely ignored. Therefore, the purpose of the present study was to determine the optimal cropping pattern through an environmental approach in a case study in Kazeroun County, Fars, Iran. Data was collected from production costs statistics provided by the Statistics and Information Technology Bureau of Agriculture-Jahad Organization. The optimal cropping pattern was determined through the goal programming model with four goals of maximizing farmers’ net return, minimizing the amount of used water, chemical fertilizers, and pesticides under three scenarios. The results indicated that the third scenario which involved the environmental goals specified by the Islamic Republic of Iran’ s 5th Development Plan, was the optimal one. In this scenario, the use of water, chemical fertilizers and pesticides decreased by 4. 4%, 4. 72%, and 8. 33% respectively while the net return increased by 10%. According to the results of the study, it is possible to increase the profit and productivity of resources with regard to environmental issues.

Environmental sustainability is one of the most important considerations in planning and managing agriculture in any country nowadays. Agriculture plays an important role in Afghanistan's economy and employment. Herat province is rich in agricultural production in Afghanistan. To achieve environmental sustainability along with profitability, the present research aimed to develop an optimal cropping pattern for Afghanistan with environmental considerations. The crops studied include wheat, barley, sesame, cumin, and saffron, which accounted for more than 70 percent of the cropping area in Herat province. The goal and linear programming model were used to determine the optimal cropping pattern. The goals of reducing the use of chemical fertilizers and pesticides along with maximizing gross margins were used in the goal model with the aim of achieving environmental sustainability. The results of the linear model, aimed at maximizing gross margins, showed that in the optimal pattern of the region, the cultivated area of sesame, barley, and saffron should be increased and the cultivated area of wheat and cumin should be decreased versus the status quo. In addition, the results of goal models in different scenarios showed significant changes in comparison to the current cropping pattern.

Imprecise or fuzziness is a main characteristic of agriculture activities data, thus fuzzy logic based methods may be useful in production planning. Possiblistic programming as one of fuzzy logic based methods was applied in this study. In addition, in the framework of multi objective programming, fuzzy and deterministic programming was also considered. Applied data set was obtained from 100 randomly selected farmers of Kohgilooye and Boyerahmad province in 1378. Gross margin increment and reduction of risk were considered as objectives in developing optimal cropping pattern. Fuzzy logic was also used to choose from the different cropping patterns. Based on the results it was found that risk had high weight in developing optimal solution. Findings of the study showed that Possiblistic programming was more capable in reaching various goals simultaneously as compared to the other methods especially when farmers faced with undesirable conditions. It was also found that wheat, watermelon, melon and rice were more appropriate crops for production.

In this study environmental and farmer's objectives of Marvdasht district growers were considered jointly using multi objective programming. Different amounts were chosen for each objective and several plans were developed. Based on the results, it was revealed that, there was a trade off among objectives and a better combination of objectives is available, compare to current plan. It was also found that some patterns may be able to improve environmental objectives. Barley and tomato were recognized pioneer crops in that they may provide desirable combination of objectives, followed by wheat and rice. 

Sustainability in agriculture is determined by such aspects aseconomic, social, and environment. The multi-objectiveprogramming (MOP) model has been a widely used tool forstudying and analyzing the sustainability of agricultural systems; however, optimization models, in most applications, have touse data that are uncertain. Recently, robust optimization hasbeen used as an optimization model that incorporates uncertainty. This paper develops a framework for environmental-economicdecision-making that considers the environmental and economicsustainability criteria in determining an optimal allocation ofagricultural areas that cover an irrigation network under uncertaindata. The primary uncertain parameter of the robust model wasthe quantity of available water for each season. The applicationof the proposed model to the case study of the right fringe ofthe Nekooabad irrigation network in the province of Isfahan, Iran demonstrates the reliability and flexibility of the model. The results show that the optimal total gross margin decreaseswith higher robustness levels. To compensate for the loss ofgross margin of farmers in the robust pattern, efficiency enhancementpolicies were emphasized.

Optimal using of soil and water resources leads to their conservation and farmer's income growth. This study aims to determine the optimal cropping pattern in the farms of east rural region of Isfahan. Several goals such as maximizing cultivated area, net returns, employment, and also conservation and sustainability of the water resources were considered simultaneously. After gathering of needed data from several resources and interviewing with experts and processing them, a mathematical model was formulated by using multi criteria goal programming (GP) technique and solved by LINDO software for the study area. Based on the results, rice, sugar beet and alfalfa were eliminated from the cropping pattern and the cultivated areas of potatoes and corn were increased. Wheat, barley and silage maize have had almost the same area in both existing and optimum cropping patterns and the area of onion has been reduced. In addition, there was an increase in net returns by26.2 and 38.2 percent, employment by 15.1 and 2.2 percent and also decreasing of water consumption by 10.7 and 9.7 percent respectively in the north and south Baraan rural regions. Therefore, advising farmers to adopt such techniques could be beneficial to them and the region.

The purpose of this study is to find optimal cropping pattern in Iran, which maximizes the net income return per cubic meter of water consumed. Our aim is to achieve the efficient utilization of the scarce water resources. For attaining this goal, the method of fractional programming was applied to data collected from the site of Ministry of Jihad-E-keshavarzi, statistical center of Iran and yearbook of agriculture. This study was performed in two scenarios one under internal prices scenarios and the other under international prices scenario. The ratio of income to water consumed is taking as measure to gauge consistency rate. The findings show that the ratio of income to water consumed in fractional programming is higher than that of in linear programming. In other words, in optimum pattern of cropping the amount of water consumed is reduced considerably. Based on the findings, it can thus be concluded that we can enhance the performance of agricultural sector by adopting the appropriate pricing policies.

Determination of the cropping pattern and optimal combination of crops by diversification of cultivation, as an approach to reduce income risk given the economic issues and resources. Income risk as combination of price and performance risks is one of the most important risks for farmers. In this study optimal cropping pattern of crops was determined to reduce income risk by applying risk and return measures in Gorgan County in 2018. For this purpose, the diversification-consistent DEA model based on directional-distance criterion was used. The results showed that 0.05 and 11 percent decreases, respectively, in the risk measures of the coefficient of variation and conditional value at risk. Also, a 24 percent increase of the expected profit measure in the optimal cropping pattern compared to the current pattern. Furthermore, the share of more profitable crops such as medium and long rice grain with high quality and rapeseed increased in the optimal cropping pattern and share of crops such as wheat and potatoes decreased. Due to the 60 percent share of medium and long rice grain with high quality in the optimal pattern, it is recommended to use tools such as income insurance and compensating for the development of rice cultivation in the region.

Giving the importance to management of agricultural units, politics decision based on cultivation method containing the goals priority of agricultural units will get important and selecting a method which can include variety of managers goals and guide them to optimum goals is so important and serious. Therefore, in this study to determine the optimum model using linear programming method (single goal) and planning CGP (Multi choice goal) have placed. Information required through completing 188 questionnaires from farmers functions two-stage cluster sampling Torbat-of-classified to 1394, respectively. The results showed that the cultivation of wheat to the primary level increased and decreased alfalfa product. Barley in small and medium-scale crop farms and large farms without change to the primary level has increased and sugar beet in small-scale farms and in the fields of medium and large scale increase is unchanged means pattern is removed. The cotton crop in small farms and farms of medium and large scale unchanged compared to the initial level decreased.