文章基本信息

标题：A new MCDM-based approach using BWM and SAW for optimal search model
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作者：Sotoudeh-Anvari, A. ; Sadjadi, S. ; Molana, S. 等
期刊名称：Decision Science Letters
印刷版ISSN：1929-5804
电子版ISSN：1929-5812
出版年度：2018
卷号：7
期号：4
页码：395-404
DOI：10.5267/j.dsl.2018.2.001
语种：English
出版社：Growing Science Publishing Company
摘要：Search for lost or hidden things is a very interesting and complicated issue. This problem concentrates on the study of how to exploit resources to discover a target with unknown location. On the other hand, search problem may be formulated as a difficult decision problem because it is affected by various crucial decision factors such as search cost, search time, the probability of discovering, etc. In this paper, a new multi-criteria decision making (MCDM) approach on the basis of best-worst method (BWM) and simple additive weighting (SAW) is suggested to rank potential locations of lost or hidden targets. BWM is a novel subjective weighting technique and compared to the most common subjective method, analytic hierarchy process (AHP), requires fewer comparisons and gives more trustworthy outcomes. In this paper, BWM is used to gain the criteria weights and SAW is employed to rank the locations regarding the decision factors. This study demonstrates that BWM is easier and works better than AHP, also perfect agreement in the results of COPRAS, TOPSIS and SAW is observed. The suggested approach is very easy as well as flexible and provides an efficient method which can be developed to tackle other decision problems.
关键词：Search problem;Best-worst method;Subjective weighting technique;Simple additive weighting