基于遗传算法的曲面最短路径求解

对曲面上两点间最短路径的求解是一个应用非常广泛，但理论求解困难的问题。遗传算法是一种新型的、较成熟的全局随机搜索算法，具有优良的性态。该文将遗传算法引入到曲面最短路径寻优的问题中。首先在离散化的模拟数字高程上依据起点和终点，以实数编码产生一系列初始群体，定义相应的适应度函数，然后对群体进行复制、交叉和变异等操作，求解出一条曲面上两点间的最短路径。在文章的最后给出了一个数值仿真实例来了证明该算法的有效性和实用性。

Genetic Algorithm Based Shortest Path Planning on Curved Surface

The shortest path planning between two points on curved surface is a problem widely used but difficult in theory. Genetic algorithm is a global stochastic searching algorithm, new and mature, with excellent state. Therefore, in this paper, the GA is used to the search of the shortest path on curve surface. Firstly, according to the start point and end point on the discrete simulation digital altitude, we produce a series of initial populations by real numbers coding, then define the fitness function and perform copy, crossover and mutation operations on the populations. As a result, the shortest way between two points on curve surface is achieved, A numerical simulation example is presented at the end of the paper in order to testify the effectiveness and validity.