Optimal allocation of agricultural land for crop planning in Hirakud canal command area using swarm intelligence techniques

Abstract

ABSTRACT The present study investigates the prevailing cropping pattern, adopted by the farmers of the study area under consideration. It aims at improving the net benefits from the farming activities with present irrigation water allocation. To arrive at the optimal cropping pattern, various swarm intelligence techniques, genetic algorithm (GA), cuckoo search (CS) and particle swarm optimization (PSO) techniques are used to formulate an efficient cropping pattern for maximizing net return for the part of Hirakud command area, in India. Maximum available land area, water for irrigation and cropping area for different crops were considered as constraints. The results are compared with the output from linear programming (LP) to evaluate the efficiency of the models. The results reveal that the net economic return arrived at by adopting the optimal cropping pattern derived with the use of PSO works out to be 230.120 Billion Rupees, whereas it is 132.2 Billion Rupees from the prevailing crop pattern adopted by farmers; 199.271 Billion Rupees with the application of LP; 210.19 billion rupees with GA and 229.895 billion rupees with CS. Weightage is given to a given crop under consideration by allocating suitable land area as per the type of land and water availability.