The Application of the Genetic algorithm-Ant algorithm in the Geometric Constraint SatisfactionGuidelines

摘要

The constraint problem can 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 fully the parallel, feedback and the high solving efficiency. Using random colony in the genetic algorithm, this 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