基于投影寻踪的组合评价方法研究

以理想解法和灰色关联度分析法为基础进行组合，得到的组合评价方法能够提高评价结果的有效性。在该组合评价方法的研究中，常规的作法是对指标组合权重的运用主观赋值法，组合的偏好系数、灰色关联度的分辨系数采取人为赋值法，没能充分挖掘组合评价方法的优势。针对此问题，提出用投影寻踪法构建处理组合评价法的优化模型，运用实码加速遗传算法处理该非线性优化问题，所得的指标权重为客观权重，同时得到确定组合评价法组合偏好系数和灰色关联度分辨系数的新方法。实例表明，基于投影寻踪的组合评价方法具有科学性和客观性。

Combinational Evaluation Method Based on Projection Pursuit Algorithm

The combinational evaluation method which combines TOPSIS with gray correlation degree analysis can improve validity of the evaluation result. In such method, a usual way to assign combinational weight of index is subjective weighting, to assign combinational preference coefficient and identification coefficient is manual weighting. The advantages of combinational evaluation method are not fully mined. Aim at this problem, a method uses projection pursuit algorithm to establish combinational evaluation model is presented. The real coded accelerating genetic algorithm is used to dispose those non-linear problems. The gained index weights are objective. In the same time, a new method of confirms combinational preference coefficients and identification coefficients of gray correlation degree is presented. The example shows the combinational evaluation method based on projection pursuit algorithm is scientific and objective.