Optimization Research on Crop Planting Strategies Based on Multi-objective Optimization Model and Game Theory

Zihan Fu; Langjie Qiao; Yanjie Gao

doi:10.54097/73jmrj19

Authors

Zihan Fu
Langjie Qiao
Yanjie Gao

DOI:

https://doi.org/10.54097/73jmrj19

Keywords:

Planting strategy optimization, Target-MOTAD model, Hybrid genetic algorithm, Principal-agent game, NSGA-II.

Abstract

This paper aims to promote rural revitalization and support the long-term development of national agriculture by optimizing planting strategies, developing organic farming according to local conditions, and rationalizing the use of cultivated land. Based on the data related to cultivated land area in North China from 2017 to 2022, a multi-objective function optimization model is constructed, which comprehensively considers constraints such as land type, crop planting area limitations, crop continuous cropping effects, and legume crop rotation requirements. On this basis, the target-MOTAD model and importance sampling-Monte Carlo simulation are introduced to establish a comprehensive objective function for maximizing revenue and minimizing risk, which is solved by a hybrid genetic algorithm. Furthermore, complementarity coefficients and substitution coefficients are introduced to establish a market response model based on principal-agent game, which is dynamicized and solved by the NSGA-II algorithm, aiming to provide scientific decision support for agricultural producers and improve their revenue.

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