Genetic algorithm for minimum weight triangulation based on dynamic programming

被引：0
|
作者：
Zhang, DM [1 ]
Gao, CQ [1 ]
Yu, DJ [1 ]
Gao, W [1 ]
Hong, X [1 ]
机构：
[1] China Univ Geosci, Dept CS, Wuhan 430074, Peoples R China
来源：
Progress in Intelligence Computation & Applications | 2005年
关键词：
the minimum weight triangulation; genetic algorithm; Dynamic Programming; mutation operator;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The problem of computing the minimum weight triangulation of a point set is known to be NP-Hard. In this paper, an improved genetic algorithm is presented to find an approximate solution to this problem. We use a new mutation operator based on Dynamic Programming to compute a largest sub-triangulation during evolution, which is much more efficient compared with the traditional flip method. The experimental results always show improvements to those traditional algorithms, such as the Greedy Method.
引用
收藏
页码：229 / 235
页数：7
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