作　　者： ;

机构地区： 华南理工大学工商管理学院

出　　处： 《华南理工大学学报（自然科学版）》 1994年第5期127-131,共5页

摘　　要： 本文在本篇论文第一部份［１］的基础上，讨论了如何通过缩小路径起点的取值范围来缩小搜索范围，以达到既减少计算量，又能取得较大的搜索最优路线成功概率之目的．本文利用数据处理技术中Ｚｉｐｆ定律的有关假设与结论，证明了：当城市数目ｎ增大时，用本算法得出的最优解逐渐趋近于在原来未缩小的搜索范围内得到的最优解，而由本文确定的实际搜索范围远远地小于原搜索范围。 On the base of the first part of this topic, the discussion in this paper is how to minimize path search region by decreasing the selected number of start point of the path, in order to achieve the aim not only minimizing calculating work but also making the search of optimal path have a larger successful probability. In addition, by utilizing the relative hypothesis and conclusion of Zipf law of date processing technique, it has been proved that when the number of cities increases, the optimal solution of this algorithm gradually tends to the optimal solution of the algorithm with original unminimized search region. The praCtical minimized search region in this algorithm is far smaller than that of the original one.

关 键 词： 游路问题 算法分析 搜索范围 最优化算法

领　　域： [理学] [理学]