Multi-Objective Planting Structure Optimisation in an Irrigation Area Using a Grey Wolf Optimisation Algorithm

Abstract

To improve agricultural production efficiency, increase farmers’ income, and promote sustainable development, we established a multi-objective optimisation model for crop planting structure in an irrigation area using the grey wolf optimisation (GWO) algorithm to comprehensively consider the resource, economic, and social objectives associated with agriculture. This model was subsequently applied to obtain the optimal planting structure in the southern bank of the Xiaolangdi Reservoir irrigation area in Henan Province, China. The planting areas of wheat, corn, autumn miscellaneous, and economic crops are 30,417; 25,050; 7157; and 1789 hm2, respectively. The irrigation water is 8292.66 × 104 m3, output value of crops is 105,721.37 × 104 CNY, and crop yield is 34,280.31 × 104 kg. Different solutions are used to solve the model to evaluate the results, and the order degree entropy method is used to evaluate and compare the results of multiple solutions. The optimisation scheme obtained with this model is consistent with the evaluation results of the cooperative game optimisation scheme, and the relative order degree entropy is 0.136, which is better than that in other schemes. Thus, the optimisation scheme of crop planting structure obtained via GWO comprehensively considers irrigation water consumption, economic benefits, and crop yield, which ensures coordinated development of resource, economic, and social systems and is conducive to promoting the benign development of the whole irrigation area system.