文章基本信息

标题：A new fuzzy mathematical model for multi criteria decision making: An application of fuzzy mathematical model in a SWOT analysis
本地全文：下载
作者：Dragan Pamučar ; Goran Ćirović ; Dragoljub Sekulović 等
期刊名称：Scientific Research and Essays
印刷版ISSN：1992-2248
出版年度：2011
卷号：6
期号：25
页码：5374-5386
DOI：10.5897/SRE11.1402
语种：English
出版社：Academic Journals
摘要：Analysis of strengths, weaknesses, opportunities and threats (SWOT) is a method to formulate the strategy. Although the SWOT analysis successfully provides the key factors of the problem, it has some drawbacks in selecting appropriate strategy for the evaluation and final decision steps. During recent years, some multiple criteria decision making (MCDM) remove some of these deficiencies, but the nature of these decision usually is very complex and using crisp datais not suitable. In this paper, linguistic variable represented with fuzzy numbers are used to assess the ratings and weights. This paper presents a new fuzzy mathematical model for evaluating the proposed alternatives. Fuzzy linguistic descriptors were used for describing the criteria. In this way, fuzzy logic enables the exploitation of tolerance that exists in imprecision, uncertainty and partial truth of the acquired research results. The paper presents a model for designing the organisational structure of transport support authorities in the Serbian Armed Forces. Various organisational structure options are proposed in application of the given model, taking into account the fact that transport authorities should be designed and dimensioned so as to achieve the rudimentary goals and tasks for fulfilment of which they were established. Each task set before the transport authorities requires reliable and top-quality performance in all environmental conditions. Since most of the acquired data is characterized by a high degree of imprecision, subjectivity and uncertainty, fuzzy logic was used for displaying these.
关键词：Strengths; weaknesses; opportunities and threats analysis; organizational structure design; fuzzy logic; multi-criteria decision making