| 用改进的遗传算法求解中国旅行商问题 |
| |
| 引用本文： | 潘立登 黄晓峰. 用改进的遗传算法求解中国旅行商问题[J]. 北京化工大学学报(自然科学版), 1997, 24(1): 62-66 |
| |
| 作者姓名： | 潘立登 黄晓峰 |
| |
| 作者单位： | 北京化工大学自动化系!北京，100029，北京化工大学自动化系!北京，100029 |
| |
| 摘 要： | 遗传算法是基于生物进化原理的普适性全局优化算法，针对一类ＮＰ完全的组合优化问题－旅行商问题，提出用交换算子操作和模拟退火思想对遗传算法进行改进，显著提高了算法的优化效率，到目前为止，中国旅行商问题的最优解是１５４２６ｋｍ，使用改进的遗传算法，仅利用城市间的距离信息求解中国诱行商问题，得到了１５４０９ｋｍ的更优结果。
|
| 关 键 词： | 遗传算法 组合优化 中国旅行商问题 解 最佳化 |
Solving Chinese Traveling Salesman Problem with Improved Genetic Algorithms |
| |
| Pan Lideng,Huang Xiaofeng. Solving Chinese Traveling Salesman Problem with Improved Genetic Algorithms[J]. Journal of Beijing University of Chemical Technology, 1997, 24(1): 62-66 |
| |
| Authors: | Pan Lideng Huang Xiaofeng |
| |
| Abstract: | Genetic Algorithms (GAs)are general-purposeeglobal optimization algorithmsbased on natural evolution rinciple In thisspaple, focusing on a kind of NP completecombinahon optimum problem--Travelling Salesman Problem (TSP), exchange operatorand simulated annealing method are introduced into GAs to approve optimum efficiency.UP to now, the best result of Chinese, TSP is 15 426 km. Only distances between all the cities are used in the improved GAs, and an even better result, 15 409 km,has been obtained. |
| |
| Keywords: | genetic algorithms combination optimum traveling salesman problem exchange operator simulated annealing |
| 本文献已被 CNKI 维普 等数据库收录！ |
