Multi-objective Optimization and Grey Wolf Optimize for Enhanced Cultivation Strategy Development

Considering the uncertainties and planting risks of sales volume, yield per mu, planting cost and selling price, this paper determines how to make the optimal crop planting plan for a village from 2024 to 2030. We use the multi-objective programming model to solve the problem. Combined with the data, we listed three objective functions: maximization of planting income, minimization of management difficulty and minimization of unsalable loss. We carried out basic constraints on planting area, planting varieties and planting methods according to the requirements of the topic, and designed constraint conditions for the unsalable situation. 0-1 variable m was introduced to measure whether a certain factor would affect the growth rate of a certain crop. Finally, a multi-objective programming equation for solving the slow sales problem is obtained. Finally, grey Wolf optimization algorithm was used to solve the multi-objective programming equation, and finally the planting plan of the village crops in 2024∼2030 was obtained.