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Optimization of Agricultural Machinery Allocation in Heilongjiang Reclamation Area Based on Particle Swarm Optimization Algorithm

机译:基于粒子群优化算法的黑龙江垦区农业机械配置优化

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Aiming at the imbalance of seasonal agricultural machinery operations in different regions and the low efficiency of agricultural machinery, an experiment is proposed to use particle swarm algorithm to plan agricultural machinery paths to solve the current problems in agricultural machinery operations. Taking the harvesting of autumn soybeans at Jianshan Farm in Heilongjiang Reclamation Area as the experimental object, this paper constructs the optimization target model of the maximum net income of farm machinery households, and uses particle swarm algorithm to carry out agricultural machinery operation distribution and path planning gradually. In this paper, by introducing 0 - 1 mapping, the improved algorithm adopts continuous decision variables to solve the optimization of discrete variables in agricultural machinery operations. The test results show that the particle swarm algorithm can realize the optimal allocation of agricultural machinery path, and the particle swarm algorithm is scientific and explanatory to solve the agricultural machinery allocation problem. This research can provide a scientific basis for farm agricultural machinery allocation and decision analysis.
机译:针对不同地区的季节性农业机械运营的不平衡和农业机械的低效率,提出了使用粒子群算法来规划农业机械路径来解决农业机械运营中的当前问题。在黑龙江填海区江山农场采集秋豆浆机作为实验对象,本文构建了农户最大净收入的优化目标模型,采用粒子群算法进行农业机械运行分配和路径规划逐步地。本文通过引入0-1映射,改进的算法采用连续判定变量来解决农业机械运营中离散变量的优化。测试结果表明,粒子群算法可以实现农业机械路径的最佳分配,粒子群算法是解决农业机械分配问题的科学和解释。该研究可以为农业农业机械配置和决策分析提供科学基础。

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