Article ID: | iaor200717 |
Country: | United Kingdom |
Volume: | 44 |
Issue: | 10 |
Start Page Number: | 2047 |
End Page Number: | 2069 |
Publication Date: | Jan 2006 |
Journal: | International Journal of Production Research |
Authors: | Wang J., Lin H.-Y. |
Keywords: | decision theory, heuristics: genetic algorithms |
Due to reducing product life cycle and increasing product complexity, design chain management has become more important for industries to develop innovative products within a shorter lead-time. Selecting the design chain partners that is a key determinant of co-development success involves multiple selection criteria and constraints that are either qualitative or quantitative. Poor selection of design chain partners may cause higher development time and cost and less competitive products. This paper considers design chain partnership formation as a multi-criteria decision-making problem. Fuzzy set theory is used to represent information that is mostly imprecise and uncertain at this stage. A fuzzy hybrid decision-aid model that integrates a fuzzy multi-criteria outranking approach with a fuzzy integer programming model is proposed to tackle both qualitative and quantitative factors as well as the decision flexibility. A genetic algorithm approach is applied to select the set of partners that maximise the total performance score of the entire design chain and satisfy the constraints of target development time and cost at the same time. An example of mobile phone design chain is used to illustrate the developed concept.