A non-dominance-based online stopping criterion for multi-objective evolutionary algorithms

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, ther...

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Bibliographic Details
Published in:International journal for numerical methods in engineering 2010-11, Vol.84 (6), p.661-684
Main Authors: Goel, Tushar, Stander, Nielen
Format: Article
Language:English
Subjects:
Computational efficiency
Convergence
Crashworthiness
evolutionary algorithm
Evolutionary algorithms
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
genetic algorithms
Inelasticity (thermoplasticity, viscoplasticity...)
Mathematical models
Mathematics
Methods of scientific computing (including symbolic computation, algebraic computation)
multi-objective
Numerical analysis
Numerical analysis. Scientific computation
Optimization
Physics
Sciences and techniques of general use
Searching
Solid mechanics
stopping criterion
Structural and continuum mechanics
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Summary: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 © 2010 John Wiley & Sons, Ltd.
ISSN:0029-5981
1097-0207
1097-0207
DOI:10.1002/nme.2909