Open Access
SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
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The article was published on 2002-01-01 and is currently open access. It has received 1972 citations till now. The article focuses on the topics: Pareto principle & Multi-objective optimization.read more
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Journal ArticleDOI
An Interactive Evolutionary Multiobjective Optimization Method Based on Progressively Approximated Value Functions
TL;DR: Results on two- to five-objective optimization problems using the progressively interactive NSGA-II approach show the simplicity of the proposed approach and its future promise.
Journal ArticleDOI
Adaptive Replacement Strategies for MOEA/D
TL;DR: It is demonstrated that the replacement neighborhood size is critical for population diversity and convergence, and an approach for adjusting this size dynamically is developed.
Book ChapterDOI
Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization
TL;DR: Two strategies for population re-initialization are introduced when a change in the environment is detected, one to predict the new location of individuals from the location changes that have occurred in the history and one to perturb the current population with a Gaussian noise whose variance is estimated according to previous changes.
Journal ArticleDOI
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
TL;DR: A survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems and identifies and discusses some promising elements and major issues among algorithms in the Literature related to using an approximation and numerical settings used.
Journal ArticleDOI
Evolutionary multi-objective optimization in water distribution network design
TL;DR: A comparative study of three common evolutionary multi-objective optimization methods with application to water distribution system design and a comparison of the non-dominated fronts achieved by the different methods.