4.5 Article

A Multiobjective Optimization Approach for Product Line Design

Journal

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
Volume 58, Issue 1, Pages 97-108

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEM.2010.2048909

Keywords

Conjoint analysis (CA); multiobjective genetic algorithm (MOGA); product line design; utility

Funding

  1. Research Grant Council of the Hong Kong Special Administrative Region, China [PolyU 5190/06E]
  2. National Science Foundation of China [70871020, 70721001, 70625001]

Ask authors/readers for more resources

Product line design is a key decision area that a product development team has to deal with in the early stages of product development. Previous studies of product line design have focused on single-objective optimization. However, several optimization objectives may be simultaneously pursued, and the solutions that can address the objectives are required in many practical scenarios. In this research, we propose a one-step multiobjective optimization approach for product line design. The proposed optimization model has three objectives: 1) maximizing the market share of a company's products; 2) minimizing the total product development cost of a product line; and 3) minimizing the total product development cycle time. A curve-fitting method is introduced into the part-worth utility models so that the optimization model can be applied to products with level-based attributes and attributes that have continuous values. A multiobjective genetic algorithm is adopted to solve the optimization model, obtaining a set of nondominated solutions. With the solutions, a new product development team can select a preferred solution interactively in a 2-D graph. An example of the optimal design of a product line of digital cameras is used to illustrate the proposed approach.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available