产品规划中基于模糊效用偏好的顾客需求优先性分析

陈振颂; 李延来; 李思丰; Kwai-Sang Chin

产品规划中基于模糊效用偏好的顾客需求优先性分析

1.
西南交通大学交通运输与物流学院, 成都 610031;
2.
西南交通大学综合交通运输智能化国家地方联合工程实验室, 成都 610031;
3.
Department of System Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong

基金项目:

国家自然科学基金项目(71371156,70971017)

西南交通大学优秀博士学位论文培育项目资助

详细信息

作者简介:
陈振颂(1988-)，博士研究生，研究方向为产品设计与管理和决策分析，czs7328026@126.com;李延来(联系人)，教授，博士生导师，lyl-2001@163.com

陈振颂(1988-)，博士研究生，研究方向为产品设计与管理和决策分析，czs7328026@126.com;李延来(联系人)，教授，博士生导师，lyl-2001@163.com

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- 文章访问数: 108
- HTML全文浏览量: 23
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- 被引次数: 0
出版历程
- 收稿日期: 2012-10-11
- 刊出日期: 2015-06-10

Customer Requirement Priority Analysis Based on Fuzzy Utility Preferences in PPHOQ

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031;
2.
Nation and Region Combined Engineering Laboratory of Intelligentizing Integrated Transportation, Southwest Jiaotong University, Chengdu 610031;
3.
Department of System Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong

摘要

摘要: 顾客需求市场竞争性分析是更为准确地确定顾客需求最终重要度的必要步骤,其有效性将直接影响产品规划质量屋的构建精确度。针对该分析过程中顾客对于竞争性产品偏好信息的模糊性,提出基于非对称三角模糊效用偏好的顾客需求竞争性评价矩阵的确定方法。利用三角模糊数中所定义的"距离"概念,构建以顾客需求竞争评价信息总相离度最大化为目标的单目标优化模型以确定顾客需求竞争性优先度。采用拉格朗日函数求解此优化模型,并对求解结果进行归一化处理以获取归一化的顾客需求竞争性优先度。通过与经典信息熵方法进行对比,论证了该方法的适用性及优势。
- 质量屋 /
- 模糊效用偏好 /
- 竞争性优先度
Abstract: Market competition analysis of customer requirements (CRs) is a necessary step to determine final im-portance ratings of CRs more precisely, and its effectiveness will directly affect the accuracy of building house of quality (HOQ). Firstly, based on asymmetric triangular fuzzy utility preferences for each competitive product offered by each customer, a new method to establish fuzzy competitive evaluation matrixes of CRs corresponding toeach customer was proposed. Secondly, according to a principle of fuzzy deviation between two asymmetric triangular fuzzy numbers, a single－objective optimization model which aims at maximizing the total similarities of fuzzy competitive evaluations was constructed by using fuzzy competitive evaluation matrixes. Finally, this model was resolved by using Lagrange function, and then normalized competitive priority ratings of CRs were obtained.The proposed approach was illustrated to its feasibility and superiority with a help of an example of vibrating feeder produced by a mechanical engineering enterprise and compared with the information entropy one.
- MATLAB /
- matrix algebra /
- quality function deployment

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