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首页> 外文会议>International conference on systems science and systems engineering >CONSISTENCY IMPROVING MODELS AND ALGORITHMS IN THE ANALYTICAL HIERARCHY PROCESS
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CONSISTENCY IMPROVING MODELS AND ALGORITHMS IN THE ANALYTICAL HIERARCHY PROCESS

机译：分析层次过程中的一致性改进模型和算法

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The modification to the inconsistent comparison matrix (ICM) in the Analytical Hierarchy Process (AHP) is concerned. Two modification optimization models and algorithms are put forward according to two preservation criteria, which can decrease the consistency ratio (CR), can offer more possible suggestions for a decision maker (DM), importantly can preserve most information that the original matrix contains. The idea of the first model is the departure should be limited between the improved matrix and the original matrix. To one entry, let it extend some distance towards right and left directions respectively, then, the original matrix will be converted into the interval number comparison matrix after all entries are extended. The matrix with the minimum CR inside the interval number comparison matrix can be taken as the improved matrix. Based on the above-mentioned idea, a computation model is put forward. The model is a nonlinear program and the genetic algorithm is designed. The second model focuses on the matrix contains the Unusual and False Observations (UFO) entry. In this case, the key problem is to find the UFO entry. To solve this problem, the relationship between the CR and one given entry is analyzed. Next, a modification algorithm is developed.
机译：对分析层次结构（AHP）中的对不一致的比较矩阵（ICM）的修改涉及。根据两个保存标准向前提出了两个修改优化模型和算法，这可以降低一致性比（CR），可以为决策者（DM）提供更多可能的建议，重要的是可以保留原始矩阵包含的大多数信息。第一个模型的思想是偏离应限于改进的矩阵和原始矩阵之间。到一个条目，让它分别向右和向左方向扩展一些距离，然后，在所有条目扩展后，原始矩阵将被转换为间隔数比较矩阵。具有间隔数比较矩阵内的最小CR的矩阵可以作为改进的矩阵。基于上述思路，提出了计算模型。该模型是非线性程序，设计了遗传算法。第二种模型侧重于矩阵包含不寻常和错误的观察（UFO）条目。在这种情况下，关键问题是找到UFO条目。为了解决这个问题，分析了CR与一个给定的条目之间的关系。接下来，开发了一种修改算法。

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