Abstract: The ant colony algorithm is a swarm intelligence optimization algorithm which is proposed by Marco，Dorigo and other scholars inspired by the foraging behavior of real ants.In order to improve the recall and precision of the search engine，both the theoretical analysis and experimental method are used to study the application of ant colony algorithm in the search engine system.The paper quantifies the users’ favoritism by ant group algorithm，and proposes a multi-objective optimization model for comprehensive assessment system of the website which is based on three indexes of the link structure of website，the content correlation and the users’ favoritism.It theoretically describes the feasibility and adaptability of the application of ant colony algorithm in the search engine system，and finally the simulative experiments have proved the effectiveness and superiority of the comprehensive assessment system of the website.

Key words: ant group algorithm, search engine, multi-objective optimization

摘要： 蚁群算法是Marco和Dorigo等学者在真实蚂蚁觅食行为的启发下提出的一种群智能优化算法。为了提高搜索引擎系统中的查全率和查准率，采用理论分析和实验相结合的方式，研究了蚁群算法在搜索引擎系统中的应用。引用蚁群算法量化用户偏爱度，提出了一种基于网页的链接结构、内容关联度和用户偏爱度三个指标的多目标优化模型的网页价值综合评价体系。从理论上阐述了蚁群算法应用于搜索引擎系统的可行性及适应性。最后实验仿真证明了该网页价值综合评价策略的有效性和优越性。

关键词: 蚁群算法, 搜索引擎, 多目标优化