An improved MOEA/D algorithm for bi-objective optimization problems with complex Pareto fronts and its application to structural optimization

•An improved MOEA/D (iMOEA/D) is proposed for bi-objective optimization problems with complex Pareto fronts.•An adaptive replacement strategy and a stopping criterion are integrated into iMOEA/D.•iMOEA/D is evaluated using seven complicated benchmark functions and three practical problems.•iMOEA/D g...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 92; pp. 430 - 446
Main Authors:	Ho-Huu, V., Hartjes, S., Visser, H.G., Curran, R.
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 01.02.2018 Elsevier BV
Subjects:	Benchmarks Complicated Pareto fronts (PFs) Decomposition Design optimization Evolutionary algorithms Genetic algorithms Mopping Multi-objective evolutionary algorithm (MOEA) Multi-objective evolutionary algorithm based on decomposition (MOEA/D) Multiple objective analysis Pareto optimization Structural optimization Truss structures Multi-objective evolutionary algorithm (MOEA) Multi-objective evolutionary algorithm based on decomposition (MOEA/D) Complicated Pareto fronts (PFs) Structural optimization Truss structures
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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