Abstract
An adaptive product platform offers high customizability for generating feasible product variants for customer requirements. Customization takes place not only to product platform structure but also to its relevant parameters. Structural and parametric optimization processes are interwoven with each other to achieve the total optimality. This paper presents an evolutionary method dealing with interwoven structural and parametric optimization of adaptive platform product customization. The method combines genetic programming and genetic algorithm for handling structural and parametric optimization, respectively. Efficient genetic representation and operation schemes are carefully adapted. While designing these schemes, features specific to structural and parameter customization are considered for the simplification of platform product management. The experimental results show that the performance of the proposed algorithm outperforms that of the tandem evolutionary algorithm in which a genetic algorithm for parametric optimization is totally nested in a genetic programming for structural optimization.
| Original language | English |
|---|---|
| Pages (from-to) | 650-658 |
| Number of pages | 9 |
| Journal | Robotics and Computer-Integrated Manufacturing |
| Volume | 23 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Dec 2007 |
| Externally published | Yes |
Keywords
- Evolutionary algorithm
- GBOM
- Genetic algorithm
- Genetic programming
- Platform product customization
- Product platform
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- General Mathematics
- Computer Science Applications
- Industrial and Manufacturing Engineering