Identification of optimal crop plan using nature inspired metaheuristic algorithms

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  • Kamalika Nath Ph D Scholar, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • Rajni Jain Principal Scientist, ICAR-NIAP
  • Sudeep Marwaha Principal Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • Himadri Shekhar Roy Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • Alka Arora Principal Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India


Crop plan, Differential Evolution (DE), Genetic Algorithm (GA), Linear programming, Metaheuristic, Particle Swarm Optimization (PSO)


The present study deals with the identification of optimal crop plan to improve the net benefits from the farming activities for the study area under consideration.Three nature inspired metaheuristic techniques namely Differential Evolution (DE), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are investigated to identify the most efficient crop plan to maximize the net farm benefits. Different resource constraints considered for the study are maximum available land area, ground water availability and cropped area for different crops. The obtained results are compared with the solutions from LINGO, software for Linear Programming (LP). The results reveal the net benefit per ha derived using DE, PSO, GA and LINGO are 73841.69, 73439.08, 70555.99 and 73841.65 Indian Rupees (INR) respectively for kharif crops and 20184.71, 20172.78, 19860.80 and 20184.70 `Indian Rupees (INR) respectively for rabi crops.


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How to Cite

Nath, K., Jain, R., Marwaha, S., Roy, H. S., & Arora, A. (2020). Identification of optimal crop plan using nature inspired metaheuristic algorithms. The Indian Journal of Agricultural Sciences, 90(8), 1587-1592.