The Application of the Genetic Algorithm-Ant Algorithm in the Geometric Constraint Satisfaction Guidelines
The constraint problem can be be transformed to an optimization problem. We introduce GAAA (genetic algorithm-ant algorithm) in solving geometric constraint problems. We adopt genetic algorithm in the former process of algorithm so that it can make use of the fastness, randomicity and global stringency of genetic algorithm. Its result is to produce the initiatory distribution of information elements. The latter process of the algorithm we adopt ant algorithm. In the condition that there are some initiatory information elements, we can utilize Jully the parallel, feedback and the high solving efficiency. Using random colony in the genetic algorithm, mis can not only improve the speed of ant algorithm but also avoid getting in the local best solution when solving the precise solutions. The algorithm has a good effect in not only optimization capability but also time capability.Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially.
Cao Chunhong Zhang Bin Wang Limin Li Wenhui
Information Science and Engineering, Northeastern University, Shenyang 110004, P.R.China Computer Science and Technology, Jilin University, Changchun 130012, P.R. China
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
101-106
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）