Di Wang

Pesticides are indispensable in agricultural production, as they not only effectively prevent pests and diseases, safeguarding crops from damage, but also regulate plant growth, thereby boosting crop yield and quality. Nevertheless, the improper use of pesticides and the persistence of residues pose severe threats to ecological health and environmental sustainability. This study constructs a multi-objective optimization model to mitigate pesticide reliance and promote precision application. This model considers three key factors: pesticide cost, therapeutic efficacy, and spraying frequency. We introduce a multi-objective optimization framework to outline the problem-solving approach systematically. Additionally, through a series of performance metrics, we comprehensively analyze and compare different algorithms and constraint handling techniques. The experimental results validate the rationality and effectiveness of the developed mathematical model. It offers practical and valuable guidance for optimizing pesticide spraying operations, helping to balance agricultural productivity, and environmental protection.