The algorithms of Bottom-Up grid and Top-Down grid are all high-performance anonymous algorithms based on grid-partitioning space. Different algorithm needs different parameter criteria, such as iterations, the size of anonymous area, and the users’ degree of anonymity. These parameters have great impacts on query quality, but they are conflicting. When mobile users transmit location service requests under different situations, they may have their own individual requirements about these parameters. To solve the problem, on the basis of the algorithms of Bottom-Up grid and Top-Down grid, this paper gives a method of optimization selection based on personalized space anonymous algorithm. Firstly, the method constructs a mathematical model of these parameters according to the AHP. Secondly, it structures a straight reciprocal matrix based on the user’s review of these parameters and checks the consistency. Lastly, it performs experiments and simulations to calculate the weights of algorithms of Bottom-Up grid and Top-Down grid, then choses the algorithm with bigger weight. The method of optimization selection not only satisifes the demand of k-degree, but also conforms to the users’ needs in different situations.%Bottom-Upgrid算法和Top-Downgrid算法都是基于网格划分空间的高效匿名算法，不同的算法其最终需要查询的迭代次数、形成的匿名区大小、用户得到的相对匿名度都有可能不同，这些因素之间的关系是矛盾的，但对查询质量都有着重要的影响。不同的移动用户在不同情况下发送位置服务请求时，对影响查询质量的迭代次数、匿名区域、相对匿名度这3个准则都有着自己的个性化要求。为了解决这个问题，文章在Bottom-Up grid算法和Top-Down grid算法的基础上提出了一种基于个性化需求的最优化算法选择方法。该方法首先根据层析分析法(AHP)对3个准则进行数学建模，然后根据用户对这3个准则的评估构造正互反矩阵并进行一致性检验，最后通过对两种算法的实验模拟，计算两种算法的权重，最终选择权重值较大的算法。此最优化选择方法在满足匿名度k的条件下也符合用户针对不同情况的个性化需求。
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