Abstract: An improved immune algorithm is proposed in order to overcome the shortcomings exited in the immune algorithm based on information entropy and Euclidean in this paper.The proposed algorithm re-defines the calculation of the density of antibody，and proposes a new strategy to maintain the diversity of the antibody group.And it is applied into the solution of Chinese Traveling Salesman Problem（CTSP），in which we proposed a new vaccine extraction and injection method.The experiments indicate that the new algorithm can converge to the optimal solution more efficient and faster in time.It is an ideal improved algorithm for solving complex optimization problems.

Key words: immune algorithm, information entropy, Euclidean distance, vaccine, Traveling Salesman Problem

摘要： 针对基于信息熵和基于欧氏距离的免疫算法存在的不足，提出了一种改进的免疫算法。该算法重新定义了浓度的计算方法，提出一种新的保持抗体群多样性的策略，在将其应用在中国旅行商问题（CTSP）的求解中，具体针对旅行商问题提出了新的免疫疫苗的提取和注射方法，通过实验表明了新的算法能更快地收敛到最优解，且求得最优解的效率更高，是一种较理想的求解复杂优化问题的改进算法。

关键词: 免疫算法, 信息熵, 欧氏距离, 免疫疫苗, 旅行商问题