Application of crisp and fuzzy goal programming models for optimization of cropping pattern in Haraz sub-basin in Iran

All of past mathematical programming methodologies are outcome of two and multi value logic. These methods want quantitative crisp information. Human senses (linguistic variable) and vague information do not exist in past mathematical models. In the year 1965 professor Zadeh oriented theory of fuzzy sets. In its origin fuzzy theory with the help of classic mathematics and standard indexes is able to give mathematical shape to the process of human being identification, which in the most cases is identified. This new theory improved the simple models in sense that it abolished their simplifying approach and hence giving them more consistency with the real world. With the invention of fuzzy theory one of the dead ends planning models was opened. In this way, the budget human is not an absolute human being, instead he/she is a fuzzy human being which thinks fuzzy and makes decision on the basis of fuzzy data. This paper notice to theory and application of fuzzy linear goal programming model in optimization cropping pattern. In order to, sum total membership all fuzzy goals are maximized in this model. Versus crisp goal programming model in this method to decision maker is permitted to determinate about membership function and its importance. Also this method is able to create consistent membership function according to expects decision maker. Technical coefficient in this model is not crisp, and changes in the limited area. This paper with analysis theory fuzzy linear goal programming, indicate application of it in optimization cropping pattern in irrigation land of Haraz sub-basin in Iran. Results indicate with create flexible RHS in model, resource allocation is bettered and land surface cropping is developed.