形式概念演化生成算法

目前仍然缺乏使用遗传算法构造概念的研究。为此，首先把形式概念的构造问题转换为以形式背景的对象幂集和属性幂集组合空间为搜索空间，以伽罗瓦联系为约束条件的约束最优化问题；然后提出一个新颖的基于遗传演化的概念生成算法——遗传概念生成算法(Geacob)。该算法采用变长结构编码，不仅满足概念形式的表示和演化过程的需要，而且使该算法具有更好的扩展性和通用性。实验表明了该遗传算法求解形式概念的可行性和有效性。

Genetic algorithm to generate formal concept

At present, there is few research literature about genetically constructing formal concept. After considering formal concept construction as an optimization with constraints of Galois connection, a new concept generating algorithm named Geacob based on genetic evolution was proposed, and its research space consisted of power sets of objects and attributes in formal context. The proposed algorithm adopting variable structure can not only reasonably formalize the concept, but also satisfy the requirements in the procedure of concept's evolution, and has consequential properties of scalability and versatility. The experimental results show that the algorithm is feasible and effective to generate formal concept.