摘要
TSP问题的应用非常广,但当前较成熟的算法大都基于局部优化,而局部优化往往无法求出最优解。所提出的算法兼顾了两父体算子与一元算子的优点,并具有免疫算法的免疫记忆功能,是一个具有较强的选择压力和适应地改变的变化算子的演化算法。与其他遗传算法和免疫算法相比具有收敛速度更快,结果更优的特点。
TSP Problem has gained large popularity these days. Yet as most developed algorithms are based on local optimization, they can not provide the best optimized solution. The algorithm, presented in this article, giving attention to advantages of both duality algorithm and unitary algorithm, has memory merit of immune algorithm, and is an improved one. It has faster speed and better result than other genetic algorithms and immune algorithms.
出处
《武汉理工大学学报（信息与管理工程版）》
CAS
2004年第1期35-37,共3页
Journal of Wuhan University of Technology：Information & Management Engineering
基金
国家自然科学基金资助项目(60204001).
关键词
反序
杂交
遗传算法
免疫算法
TSP问题
antitone
cross-fertilize
genetic algorithm
immune algorithm
TSP
