Multiple Attribute Decision-making Method Based on Preference Information and Projecting Pursuit Classification Model
Ke Wang · Jisuanji fangzhen · 2007
In view of the shortage of the present subjective and objective assigning weight methods,a new combination assigning weight approach based on the decision-maker's preference and projecting pursuit classification model was proposed. Through applying projecting pursuit classification model based on adaptive particle swarm optimization algorithm in multiple attribute decision-making problems,the multi-dimension data of decision-making problem were easily changed into low dimension space and the multi-dimension data's structure feature could be discovered. Accordingly the optimum projection direction and the value of project function could be obtained. At the same time,this approach considered the decision-maker's preference information,too. The simulation results show that the proposed approach is effective and feasible.