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Projection Pursuit Model for Dynamic Multiple Attribute Decision Problems
JIN Ju-liang, WANG Shu-juan, WEI Yi-ming
2004, (1):
64-67.
In order to determine the weights of attributes and period times in dynamic multiple attribute decision,an ideal point method based on projection pursuit for dynamic multiple attribute decision,named PP-IPM,is presented in this paper.In PP-IPM model,by using the interior information of decision matrix,decision matrices of decision schemes in three dimensions can be synthesized with projection values in one dimension which indicates comprehensive quality of decision schemes,and the decision schemes can be ordered according to the projection value of each scheme.By using real coding based accelerating genetic algorithm developed by the authors,the modeling of PP-IPM can be simplified by the realized process of projection pursuit technique,and can overcome the shortcomings of large computation amount and difficulty of computer programming in traditional projection pursuit methods.The case study shows that applying PP-IPM model driven directly by decision matrix samples data is simple,feasible,general and practical,and PP-IPM model can be applied to many dynamic multiple attribute decision problems.
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