摘要
遗传算法 (GA)是一种基于自然群体遗传机制的有效搜索算法 ,由于它在搜索空间中同时考虑许多点 ,这样就减少了收敛于局部极小的可能 ,也增加了处理的并行性。因此可以利用并行遗传算法 (PGA)研究典型的组合优化实例 -TSP问题的求解问题。该文提出一种有效的并行算法求解旅行商 (TSP)问题 ,实验结果表明 。
Genetic Algorithm (GA) is an effective searching algorithm based on genetic mechanism of natural colony, consulting simultaneously several points in searching space, GA can reduce the possibility of converging on local minimum and enhance the processing parallelization. Therefore, parallel genetic algorithm(PGA) can be used in studying the solution of typical instance about combinatorial optimization—TSP problem. In this paper, we introduce the principles of PGA and make use of PGA to TSP. The results of experiments show that the new parallel genetic algorithm is practical and efficient.
出处
《计算机仿真》
CSCD
2005年第2期82-85,共4页
Computer Simulation
关键词
并行遗传算法
旅行商问题
收敛性
组合优化
Parallel genetic algorithm
Traveling salesman problem
Convergence
Combinatorial optimization
