The use of a micro genetic algorithm (mGA)-based approach to solve a bi-objective optimization of an injection mould design problem is presented. The advantage of the mGA-based approach is that it requires fewer computational resources than a conventional GA because it has a smaller population than a conventional GA. The main drawback of the mGAbased approach is that design diversity is not secured when multi-modal and multi-objective designs are investigated. To implement the mGA-based bi-objective optimization procedure, the present study proposes a memory set, a filtering process, weight control, and reproduction from the memory set in order to explore new optimal solutions, and identify more-evenly distributed Pareto surfaces. A number of mathematical functions and a typical structural optimization problem are tested to verify the proposed strategies. The approach is subsequently applied to the bi-objective injection moulding design problem of minimizing both the maximum injection pressure and maximum pressure difference between the gate positions in the runner system.
|Number of pages||13|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture|
|Publication status||Published - 2008|
Bibliographical noteFunding Information:
We thank B. Castaing for discussions. This work has been supported by the French Ministry of Research under Grant ACI Jeunes Chercheurs 2001 and by the GDR “Phénomènes hors équilibre” of CNRS.
All Science Journal Classification (ASJC) codes
- Mechanical Engineering
- Industrial and Manufacturing Engineering