遗传算法在潜土逆转旋耕刀参数优化中的应用

Application of Genetic Algorithms in Parameters Optimization of a Submerged Reverse rotary Tiller

将建立的一种基于混合选择机制的遗传算子和引入的小生境技术应用于潜土逆转旋耕刀片几何参数和运动参数的优化设计中 ,给出了潜土逆转旋耕刀片组合参数的功耗模型 ,优化结果与实验相吻合。

Historically, the research efforts on parameters optimization of a rotary tiller have mainly concentrated on traditional methods. Many optimization problems from the traditional methods are very complex in nature, quite hard to be solved and are easily immersed in local solutions. However, genetic algorithms which imitate living beings to solve such kinds of hard optimization problems are global optimal methods. Recently, genetic algorithms as an optimization technique have received considerable attention regarding their potential for complex problems and have been successfully applied in the area of industrial engineering. Based on a simple genetic algorithm (SGA) principle, this paper developed a mixed selection operator, which applied the expect value operator to the initial and middle stages of reproduction, and the sort operator to the last stage, and also introduced niche technology into it. The method was applied in our work to optimize the geometry and motive parameters of a submerged reverse rotary tiller and found the best arrangement of these parameters. A mathematical model of a submerged reverse rotary tiller was developed and the optimal results was proved correctly by the experiments.