A Mathematical Analysis of Compromising Programming Techniques

Abstract

Agriculture is the back bone of Indian economy and provides livelihood to about 70 percent of the population and about one third of our national income gets generated in this sector. After independence, in early years, there was a problem of a food shortage. The position at the food front became a matter of concern in the early sixties. To meet the situation efforts were made to develop the agriculture sector of the economy. Toward the mid of sixties the new agriculture technology emphasizing the use of fertilizer and irrigation, ushered an era popularly could as green revaluation. However it was confined to few states and few crops. In present state, the nation's objective is not only to increase the food grain production but also to increase the employment ventures. While individual farmer may be interested in maximizing his cash income risks aversion etc. The mathematical programming approach to the modeling of agricultural decisions rests on certain basic assumptions about the situation being modeled and the decision maker himself. One fundamental assumption is that the decision maker (DM) seeks to optimize a well defined single objective. In reality this is not the case, as the DM is usually seeking an optimal compromise amongst several objectives, many of which can be in conflict, or trying to achieve satisfying levels of his goals. For instance, a subsistence farmer may be interested in securing adequate food supplies for the family, maximizing cash income, increasing leisure, avoiding risk etc. but not necessarily in that order. Similarly a commercial farmer may wish to maximize gross margin, minimize his indebtedness, acquire more land, reduce fixed costs etc.