遗传量子算法在欠约束和过约束的几何约束求解问题中的应用

the Application of Genetic Quantum Algorithm on Under-constraint and Over-constraint of Geometric Constraint Solving

几何约束求解技术是基于约束满足的参数化设计方法中最核心的技术。几何约束求解技术的好坏、性能的优劣直接关系到一个基于约束的参数化设计系统是否优良。遗传量子算法是将量子计算和遗传算法相结合的算法,采用量子位染色体的表示形式。该算法具有量子计算的量子位和量子位的迭加特性,同时加入了量子交换算法,使得进化染色体更好的呈现多样特性。实验表明,将该算法应用于几何约束求解方程中,可以解决欠约束和过约束一致的问题。

Geometric constraint solving technology is on the basis of constraint parameter design central technology, Whether the technology good and ripe or not will be the key of weighing one design system fine or not on the basis of parameter constraint system. Genetic Quantum Algorithm combines genetic algorithm with quantum computing. The algorithm is based on qubit and the superposition of qubit, and adds quantum exchange making various characteristic property of much better feasible evolution chromosome. The experiment indicates that we can use the algorithm to deal with under-constraint and over-constraint problems of general geometric constraint problem.