Journal
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
Volume 84, Issue 6, Pages 661-684Publisher
WILEY
DOI: 10.1002/nme.2909
Keywords
convergence; stopping criterion; multi-objective; evolutionary algorithm; crashworthiness; genetic algorithms
Ask authors/readers for more resources
A non-dominance criterion-based metric that tracks the growth of an archive of non-dominated solutions over a few generations is proposed to generate a convergence curve for multi-objective evolutionary algorithms (MOEAs). It was observed that, similar to single-objective optimization problems, there were significant advances toward the Pareto optimal front in the early phase of evolution while relatively smaller improvements were obtained as the population matured. This convergence curve was used to terminate the MOEA search to obtain a good trade-off between the computational cost and the quality of the solutions. Two analytical and two crashworthiness optimization problems were used to demonstrate the practical utility of the proposed metric. Copyright (c) 2010 John Wiley & Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available