问题规模化是近来信息学竞赛的一个新趋势，它意在通过扩大数据量来增加算法设计和编程实现的难度，这就向信息学竞赛的选手提出了更高层次的要求，本文试图探索一些解决此类问题的普遍性的策略。开始，本文给出了“规模化”一词的定义，并据此将其分为横向扩展和纵向扩展两种类型，分别进行论述。在探讨横向扩展问题的解决时本文是以谋划策略的“降维”思想为主要对象的；而重点讨论的是纵向扩展问题的解决，先提出了两种策略——分解法和精简法，然后结合一个具体例子研究“剪枝”在规模化问题中的应用。问题规模化是信息学竞赛向实际运用靠拢的一个体现，因此具有不可忽视的意义。-The scale of the problem is the recent informatics competition is a new trend, it intended to achieve by expanding the amount of data to increase the algorithm design and programming difficulty, which a higher level of requirements to the Olympiad players, this article attempts to explore some of thegeneral strategy to solve such problems. The paper gives the definition of the term "scale", which will be divided into horizontal expansion and vertical expansion of the two types, were discussed. Solution to explore the problem of horizontal expansion when this article is to plan strategy, "dimensionality reduction" ideology as the main object　focus on the scale of problems, the first two strategies- decomposition and streamline the law, and then combined with a specific example of "pruning" in the large-scale problems. The scale of the problem is the the informatics race closer to the practical application of an embodiment and therefore can not be ignored significance.