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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Book ChapterDOI
Population-Based Incremental Learning for Multiobjective Optimisation
Sujin Bureerat,Krit Sriworamas +1 more
TL;DR: The work in this paper presents the use of population-based incremental learning (PBIL) as a tool for multiobjective optimisation, and concludes that, with the assigned test problems, the multiobjectives PBIL methods are comparable to the previously developed algorithms in terms of convergence rate.
Proceedings ArticleDOI
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
TL;DR: The hybrid AMGA proposed in this paper is a combination of a classical gradient based single-objective optimization algorithm and an evolutionary multi-objectives optimization algorithm that is designed to balance local versus global search strategies so as to obtain a set of diverse non-dominated solutions as quickly as possible.
Proceedings ArticleDOI
Indicator-based multi-objective local search
Matthieu Basseur,Edmund K. Burke +1 more
TL;DR: The generic local search algorithm presented in this paper and the proposed indicators obtain promising results which lead to a number of future research directions.
Journal ArticleDOI
Clear and smooth path planning
TL;DR: This paper formulate the problem of path planning as two multi-objective path planning models with the focus on robot's energy consumption and path's safety, and proposes an evolutionary algorithm for solving the problems.
Optimizing the Layout of 1000 Wind Turbines
TL;DR: An accurate, efficient, and parallelizable optimization algorithm for the layout of hundreds, then 1000, turbines that is modular and therefore allows different wake effect models to be incorporated.