fuzzy linear programming

Desertification is a complex socio-economic issue resulting from the interaction of several factors. This phenomenon is always in uncertain environments and is strongly influenced by vague and implicit judgments. Therefore, the use of multi-criteria fuzzy decision-making mechanisms seems necessary in evaluating desertification strategies. On the other hand, often the input data to these devices are inaccurate and variable. So, performing sensitivity analysis on output data is an important step in such evaluations. The aim of this study was to analyze the sensitivity of priority strategies in the Yazd-Khezrabad sub-catchment in central Iran.

In order to achieve this goal, first in the framework of fuzzy multi-criteria decision-making method and with using triangular number, fuzzy pairwise comparison decision matrix was formed and the initial priority of strategies was estimated. Then the sensitivity analysis process was performed separately on the criteria and strategies in the framework of the Triantaphyllou-sensitivity analysis model. Following the determination of the most sensitive criteria and strategy, new weights of criteria and strategies were replaced based on the most sensitive criteria and strategy in the decision matrix. By calculating the weighted average of each row of the modified normalized matrix, the degree of preference or final weight of the strategies was estimated.

The results showed that the adjustment strategy in groundwater abstraction (A31) is still considered as the most important strategy as the initial results with a degree of preference of 92.9%. While the ranking of other strategies has undergone serious changes.

It is concluded that according to the mentioned macro strategy, the process of desertification can be slowed down and the destroyed areas revived by implementing aquifer projects, improving irrigation methods, land improvement, controlling the growth of industries and aquaculture crops.

The granted credits of agriculture sector are limited and the number of applicants and sub-sectors for these credits are much, therefore, this study tried to determine optimal portfolios for agricultural bank credits by using of fuzzy logic. For performance of this study, a fuzzy linear programming model based on profit maximization was used in the period of 2011-2015. In this study, two scenarios were considered for maximizing the objective function. The first scenario involves maximizing profits facilities and the second scenario involves maximizing the net intake facility (the profit rate that deducted from that the pending rate). In both scenarios, the absence of risk and existence of risk (fuzzy) is considered. The results of this study showed that due to limitations and existing laws, the current model of credits allocation of agricultural bank was not optimal and it is necessary to review in presents and amounts of credits. Also, the credits allocation model based on risks and uncertainties is closer to reality. Agricultural bank should be made part of agro-based industries, agriculture services, poultry and non-related activities with agricultural sector in the higher priorities. Also, agricultural bank considered the rate of arrears credits to avoid them.

A kind of fuzzy linear programming (FLP) model with fuzzy right hand side coefficients is presented in this study. This approach is applied to milk production system in some dairy cattle farms of Iran with the purpose of demonstrating optimization strategy in energy consumption. Based on the results of this study and the model for maximization of energy productivity index, we found the best and optimum herd sizes in each three classified farms (150 cows) as 73, 142 and 188 heads, respectively. Confronting the major problem of uncertainty in agricultural data, linear programming with fuzzy concept was taken into account. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be used for energy planning problems and moreover it is a serious competitor for other confronting conventional optimization approaches, i.e. linear programming.

Over the past few decades, several models such as the LP model have been used for managing watersheds and determining optimal cultivation pattern for agricultural planning. Management and planning methods are the most important applied tools of management science for optimal allocating resources in order to gain the most profits in the different fields including natural resources, water resources. In this research, using optimization methods, a single objective fuzzy linear programming model was used to land use optimization and a multi objective optimization model for optimal allocation of resources. The results showed that the proposed combined model can be the base for correct management of resources and decrease the amount of soil erosion to 12 percent.Also, the results indicated that under optimized condition, the area allocated to dry farming lands will decrease about 59% and the area of rangelands, irrigated agricultures, gardens and forest plantation will increase about 1%, 9%, 94% and 229% respectively. It is mentioned that the new produced model is a model which is compatible with social and economic condition of watershed and can apply for better use, conservation and rehabilitation of existent natural resources and can be introduce as model which is on the basis of environmental approach.