基于多准则的加权Sum-Dijkstra最优路径识别算法

Ting Hua, N. Abdullah
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引用次数: 9

摘要

人们需要根据自己的喜好选择一条合适的道路。通常,为了与决策者的偏好相匹配,需要涉及多个标准。本文的主要目标是基于多个标准而不是单一标准来识别最佳路径选择。Dijkstra算法是一种只考虑单一条件的最短路径算法。加权和法是解决多准则决策问题的一种加权方法。为了实现这一目标,采用加权和Dijkstra算法(WSDA),将WSM与Dijkstra算法相结合,求解多准则网络问题。本文对Dijkstra算法和WSM进行了综述,并与WSDA进行了比较。此外,还给出了两个具有相等准则值的例子来评价该方法的性能。结果表明,与Dijkstra算法相比,WSDA在相关标准方面表现更好。此外,无需考虑问题的所有备选路径即可直接找到结果。WSDA对于非数学背景的用户来说是非常友好的。它不仅适用于城市道路问题,也适用于其他网络问题,如管道和带宽网络问题。当涉及到大规模数据问题时,使用Maple软件轻松解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weighted Sum-Dijkstra's Algorithm in Best Path Identification based on Multiple Criteria
People faced decision making in choosing a suitable path for their own preferences. Usually, more than one criterion is involved in order to match with the preferences of the decision makers. The main objective of this paper was to identify the best path selection based on multiple criteria instead of a single criterion. Dijkstra’s Algorithm is a shortest path algorithm that considers a single criterion only. Weighted Sum Method (WSM) is one of the weighting methods to solve the multi criteria decision making problems (MCDM). In order to achieve the objective, Weighted Sum-Dijkstra’s Algorithm (WSDA), a combination method between WSM and Dijkstra’s Algorithm is applied to solve multiple criteria network problems. In this paper, Dijkstra’s Algorithm and WSM are reviewed and compared as to the WSDA. In addition, two examples with equal criteria values to evaluate the performances of the approach are presented. Results show that WSDA performed better in terms of the criteria concerned as it was compared to the Dijkstra’s algorithm. Moreover, the results could be directly found without considering all the alternative paths of the problem. WSDA can be user friendly to users from non-mathematical background. It is not only applicable to urban road problems, but other network problems such as pipelines and bandwidth network problems. When come to large scale data problems, Maple software is used to solve it with ease.
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