Multi-objective optimization and design of integrated farming systems using goal programming

In the present study, the farmers’ problem and their multi-objectives were incorporated in the model by considering a case study under north Indian situations. A generalized farm problem with respect to various physical and socioeconomic constraints under irrigated ecosystem of north India was used for designing the integrated farming systems through goal programming - constraint method of modeling techniques. Maximization of farm income is selected as the main objective of the constraint method of multiobjective optimization and other two objectives, viz. capital requirement and labour employment were used as the additional constraints in the constraint set. Thirty three non-dominated set of alternatives/strategies were formulated by parametrically changing the values of additional constraints. The study revealed that the maximum farm net return of 6,59,623 was obtained, while the other two objectives, capital requirement and labour requirement were fixed as constraints at 5,24,926 and 966 man days, respectively. Goal programming can be used as tool for designing individual integrated farming system on scientific basis considering the resource availability at the farm level. The single objective IFS models were developed using linear programming technique for marginal, small and medium farm situations, which proved potential to replace existing rice (Oryza sativa L.)–wheat [Triticum aestivum (L.) emend. Fiori & Paol] system with higher profitability.