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Mixed Least Square Method for Priority of Complementary Judgement Matrix and Its Algorithm
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作者 周宏安 刘三阳 《Journal of Southwest Jiaotong University(English Edition)》 2007年第1期75-79,共5页
Based on the concept of multiplicative fuzzy consistent complementary judgement matrix, the mixed least square method (MLSM) for priority of complementary judgement matrix is proposed and proved. Then, the correspon... Based on the concept of multiplicative fuzzy consistent complementary judgement matrix, the mixed least square method (MLSM) for priority of complementary judgement matrix is proposed and proved. Then, the corresponding convergent iterative algorithm is given and its convergence is proved. Finally, some main properties of the developed priority method, such as rank preservation under strong condition, etc., ate introduced. The theoretical analyses show that the MLSM can sufficiently reflect the preference information of the decision maker, and is easy to realize on a computer. 展开更多
关键词 Multi-objective decision-making fuzzy complementary judgement matrix CONSISTENCY Mixed least square method PRIORITY
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Applying Possibility Degree Method for Ranking Interval Numbers to Partnership Selection
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作者 李彤 张强 郑涛 《Journal of Beijing Institute of Technology》 EI CAS 2008年第2期244-248,共5页
A new interval number ranking approach is applied for assessment of priorities of the alternative partners, where the attribute values are given out as interval numbers while the weight of each criterion is still exac... A new interval number ranking approach is applied for assessment of priorities of the alternative partners, where the attribute values are given out as interval numbers while the weight of each criterion is still exact numerical value pattern. After aggregating with the weighted arithmetic averaging operator, the result is still in the form of interval number. To achieve the priorities of alternative partners we take the possibility method for ranking interval numbers into account which could derive priorities from inconsistent attribute values, thus eliminating the adjustment to the inconsistent attribute values. Moreover, this method is very simple and needs less calculation. An illustrative example is given out to demonstrate this smart method. 展开更多
关键词 partnership selection virtual enterprise fuzzy complementary judgment matrix possibility degree matrix
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