CAJ | 학술논문

在分析已有关于Vague值（集）相似度量方法存在不足的基础上，综合考虑Vague值区间端点间的距离、核距离以及未知部分对支持度和反对度的影响等主要因素，提出了一种新的Vague值（集）相似度量方法，并对其性质进行讨论．通过与现有方法的比较，表明该方法具有很强的相似度区分能力．最后将所提出的Vague值（集）相似度量用于多准则模糊决策中，通过最优化方法选取每个准则的最优权重，根据候选方案与理想方案在相应准则下相似度加权和的大小得出最佳方案．通过实例分析，表明了这种方法的有效性和可行性．
재분석이유관우Vague치（집）상사도량방법존재불족적기출상，종합고필Vague치구간단점간적거리、핵거리이급미지부분대지지도화반대도적영향등주요인소，제출료일충신적Vague치（집）상사도량방법，병대기성질진행토론．통과여현유방법적비교，표명해방법구유흔강적상사도구분능력．최후장소제출적Vague치（집）상사도량용우다준칙모호결책중，통과최우화방법선취매개준칙적최우권중，근거후선방안여이상방안재상응준칙하상사도가권화적대소득출최가방안．통과실례분석，표명료저충방법적유효성화가행성．
The inadequacies of existed similarity measures between vague values （sets） are analyzed. A new similarity measure between vague values （sets）, which considers the distance of vague value interval end- points, core distance and influence of unknown part on truth-membership function and false-membership function respectively, is proposed and the properties are discussed. The new method is illustrated by comparison with the present measure methods that it has stronger discrimination of similarity measures. Finally, the similarity measures between vague values （sets） are applied to multi-criteria fuzzy decision making. The linear programming method is constructed to generate optimal weights for every criteria and the best alternative is obtained by the weighted sum of similarity measures between each alternative and the idea alternative with respect to a set of criteria. Feasibility and effectiveness of the proposed method are illustrated using a numerical example.