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Algorithmic issues in computational intelligence optimization: from design to implementation, from implementation to design
(University of Jyväskylä, 2016-08-26)
The vertiginous technological growth of the last decades has generated a variety of powerful and complex systems. By embedding within modern hardware devices sophisticated software, they allow the solution of complicated ...
A weighted biobjective transformation technique for locating multiple optimal solutions of nonlinear equation systems
(IEEE Press, 2017)
Due to the fact that a nonlinear equation system may contain multiple optimal solutions, solving nonlinear equation systems is one of the most important challenges in numerical computation. When applying evolutionary ...
Global and local surrogate-assisted differential evolution for expensive constrained optimization
(IEEE Press, 2018-03-29)
For expensive constrained optimization problems, the computation of objective function and constraints is very time-consuming. This paper proposes a novel global and local surrogate-assisted differential evolution for ...
Differential evolution with a new encoding mechanism for optimizing wind farm layout
(IEEE Press, 2017-07-11)
This paper presents a differential evolution algorithm with a new encoding mechanism for efficiently solving the optimal layout of the wind farm, with the aim of maximizing the power output. In the modeling of the wind ...
Infeasibility and structural bias in Differential Evolution
(Elsevier, 2019-05-11)
Structural bias is a recently identified property of optimisation algorithms, causing them to favour certain regions of the search space over others, independently of the objective function. Since structural bias can ...
An adaptive framework to tune the coordinate systems in evolutionary algorithms
(IEEE Press, 2018-03-12)
The performance of many nature-inspired optimization algorithms depends strongly on their implemented coordinate system. However, the commonly used coordinate system is fixed and not well suited for different function ...
Utilizing cumulative population distribution information in differential evolution
(Elsevier, 2016-07-15)
Differential evolution (DE) is one of the most popular paradigms of evolutionary algorithms. In general, DE does not exploit distribution information provided by the population and, as a result, its search performance is ...
