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随着面向对象技术应用研究的不断深入,把具有相互关系的一组数据封装在一个对象中进行统一处理的思想已经成为一种非常流行的设计方法。在实践中存在这样一种优化问题:优化变量为一组对象、且同一对象的各属性之间存在着优先级关系,即必须先确定某些属性然后才能确定其余属性,同时不同对象的属性之间也存在着许多复杂约束关系。本文从解决常规的遗传算法的不足着手,提出了面向对象遗传算法的编码策略、遗传策略以及实现方法。
With the deepening of research on the application of object-oriented technology, the idea of encapsulating a set of data with interrelationships in a single object for unified processing has become a very popular design method. In practice, there is such an optimization problem: an optimization variable is a group of objects, and there is a priority relationship between the properties of the same object, that is, certain properties must be determined before the remaining properties can be determined, and at the same time, the properties of different objects There are also many complex constraints between. In this paper, we start with the solution of the shortcomings of conventional genetic algorithms, and propose coding strategies, genetic strategies and implementation methods of object-oriented genetic algorithms.