Research of integrating supplier selection into product family planning

被引:0
作者
Cao, Y. [1 ]
Luo, X. G. [1 ]
Kwong, C. K. [2 ]
Tang, J. F. [1 ]
机构
[1] Northeastern Univ, Dept Syst Engn, State Key Lab Synthet Automat Proc Ind, Shenyang 110004, Peoples R China
[2] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Kowloon, Hong Kong, Peoples R China
来源
2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2013年
基金
美国国家科学基金会;
关键词
product family; supplier selection; multinomial logit consumer choice rule; genetic algorithm; DESIGN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the economic globalization and market constantly subdivision, the life cycle of product and the development cycle increasingly shorter. In the development process of new products, more and more scholars have realized that if suppliers collectively participate in the initial stage of product development, enterprises will effectively save the cost and the time, dramatically increase the product quality and the production flexibility. Recently, several research papers proposed some relevant methods integrating supplier selection into product family design. In this paper, a one-step unified optimization model, which integrates product family design with supplier selection, is established. The optimization model with the objective of maximizing the total profits of product family is based on multinomial logit consumer choice rule, which is regarded to be more flexible and suitable to formulate consumer choice behavior. To solve the proposed optimization model, genetic algorithm is adopted. The optimization results of integrating supplier selection and product family design and that of separating supplier selection and product family design, and the optimization results under multinomial logit rule and that under the deterministic choice rule are compared respectively. Meanwhile, in the case study, sensitivity analysis of the model is also performed.
引用
收藏
页码:4634 / 4639
页数:6
相关论文
共 14 条
[1]  
[Anonymous], 2002, Discrete choice methods with simulation
[2]   Product design with multiple suppliers for component variants [J].
Balakrishnan, Nagraj Raju ;
Chakravarty, Amiya K. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2008, 112 (02) :723-741
[3]  
Ben-Akiva M. E., 1985, Discrete choice analysis: Theory and application to travel demand, V9
[4]  
Benton W.C., 2007, Purchasing and supply management
[5]   HEURISTICS FOR PRICING AND POSITIONING A PRODUCT-LINE USING CONJOINT AND COST DATA [J].
DOBSON, G ;
KALISH, S .
MANAGEMENT SCIENCE, 1993, 39 (02) :160-175
[6]   Product variety optimization under modular architecture [J].
Fujita, K .
COMPUTER-AIDED DESIGN, 2002, 34 (12) :953-965
[7]   MODULE DESIGN WITH SUBSTITUTE PARTS AND MULTIPLE VENDORS [J].
GOLDBERG, J ;
ZHU, J .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1989, 41 (03) :335-346
[8]  
HSU TH, 2000, IEEE INT C FUZZ SYST
[9]  
Jiao J, 2007, J INTELL MANUF, V18, P5, DOI 10.1007/s10845-007-0003-2
[10]   Product portfolio planning with customer-engineering interaction [J].
Jiao, JX ;
Zhang, YY .
IIE TRANSACTIONS, 2005, 37 (09) :801-814