基于GA-PLS的产品顾客满意度优化模型

H. Ertian, Ni Yangdan
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引用次数: 0

摘要

为了解决产品性能和价格要素选择的困难以及多变量相关带来的失真问题,提出了一种基于遗传算法和偏最小二乘的产品顾客满意度优化模型。该模型不仅解决了多重共线性造成的失真问题,而且为决策者提供了多种模型。最后,将该模型应用于手机用户满意度的优化。从结果中我们可以确定哪个元素对整体满意度的影响最大,然后通过改进该元素来提高整体产品满意度。结果表明,该方法是有效的,为优化产品设计参数提供了重要依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Product Customer Satisfaction Optimized Model Based on GA-PLS
In order to solve the difficulty — how to choose elements of product performance and price — and the distortion problem caused by the multi-variable correlation, this paper proposes a optimized model of product customer satisfaction (PCS) based on genetic algorithms and partial least squares. The model not only solves the distortion problem due to multicollinearity, but also provides multiple models for policy makers. At last, the model is implemented in optimizing mobile phone’s satisfaction. From the result we can determine which element has the greatest impact on the overall satisfaction, then improve the overall product satisfaction by improving the element. The result indicates the method is effective, which has offered the important basis for optimization product design parameters.
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