关键词: 模拟植物生长算法与加速遗传算法（PGSA-RAGA）组合算法, 区间数, 群决策, 最优离合点, 投影寻踪

Abstract: For a class of multi-attribute group decision making problems, the concept of optimal clutch points is introduced according to the principle of least squares. The combining algorithm of Plant Growth Simulation Algorithm and Accelerating Genetic Algorithm （PGSA-RAGA） is used to obtain the optimal clutch points, and then the projection pursuit model is used with the matrix of the optimal clutch points to get the final projection value and the sorting results. This method solves the problem, which is usually inadequate to use the average number embodying the integrated willingness of the group decision making, in order to get the best sorting results on condition that the property of evaluation features is completely unknown. Through comparative analysis, the feasibility of this method is verified, and it is more simple and easier to operate, which effectively solves many multi-attribute group decision making problems.

Key words: Plant Growth Simulation Algorithm and Accelerating Genetic Algorithm（PGSA-RAGA） combination algorithm, interval number, group decision making, optimal clutch point, projection pursuit