Search results for "Evolutionary algorithm"

Analysis of properties of recombination operators proposed for the node-depth encoding

2011

The node-depth encoding is a representation for evolutionary algorithms applied to tree problems. Its represents trees by storing the nodes and their depth in a proper ordered list. The original formulation of the node-depth encoding has only mutation operators as the search mechanism. Although it is computationally efficient, the exclusive use of mutation restricts the exploration of the search space and the algorithm convergence. Then, this work proposes two specific recombination operators to improve the convergence of the algorithm using the node-depth encoding representation. These operators are based on recombination operators for permutation representations. Analysis of the proposed …

Nature That Breeds Solutions

2012

Nature has always been a source of inspiration. Over the last few decades, it has stimulated many successful techniques, algorithms and computational applications for dealing with large, complex and dynamic real world problems. In this article, the authors discuss why nature-inspired solutions have become increasingly important and favourable for tackling the conventionally-hard problems. They also present the concepts and background of some selected examples from the domain of natural computing, and describe their key applications in business, science and engineering. Finally, the future trends are highlighted to provide a vision for the potential growth of this field.

Velocity sensorless control of a PMSM actuator directly driven an uncertain two-mass system using RKF tuned with an evolutionary algorithm

2010

This paper proposes a solution to tune an observer keeping robust closed loop performances for the sensorless motion control of an uncertain mechanical load directly driven by a PMSM through a flexible axis. An evolutionary algorithm optimizes the observers degrees of freedom. Experiments show that performances are effectively maintained.

Fiber laser mode locked through an evolutionary algorithm

2015

Mode locking of fiber lasers generally involves adjusting several control parameters, in connection with a wide range of accessible short-pulse dynamics. In this Letter, we experimentally demonstrate the ability of an evolutionary algorithm to prescribe a set of cavity parameters entailing specific self-starting mode locking. The prescribed parameters are applied to electrically driven polarization controllers, thus shaping the effective nonlinear transfer function at play within the fiber cavity. According to the specifications of the objective function used for the optimization procedure, various short-pulse regimes are obtained. Our versatile method represents an effective novel avenue f…

A Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production

2007

This article proposes a Memetic Differential Evolution (MDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. The MDE is an adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution (DE) with the exploitative features of two local searchers. The local searchers are adaptively activated by means of a novel control parameter which measures fitness diversity within the population. Numerical results show that the DE framework is efficient for the class of problems under study and employment of exploitative local searchers is helpful in supporting the DE explorative mechanism in avoid…

Velocity sensorless control of uncertain load using RKF tuned with an evolutionary algorithm and mu-analysis

2010

Abstract In case of a velocity control scheme for a load directly driven by an actuator, large variations of its parameters are problematic due to possible instability and large variations of the final performances. This performances are then decreasing if a sensorless control is implemented due to cost, reliability or application constraints. This paper proposes solutions to quickly and accurately tune an observer with a lower computer time consumption and lower conception time. A previous calculated state feedback is used as base for a Kalman filter with special noise matrices. An evolutionary algorithm optimizes the observers degrees of freedom all over the variations. The mu-analysis th…

Evolutionary design optimization with Nash games and hybridized mesh/meshless methods in computational fluid dynamics

2012

Universal natural shapes: From unifying shape description to simple methods for shape analysis and boundary value problems

2012

Gielis curves and surfaces can describe a wide range of natural shapes and they have been used in various studies in biology and physics as descriptive tool. This has stimulated the generalization of widely used computational methods. Here we show that proper normalization of the Levenberg-Marquardt algorithm allows for efficient and robust reconstruction of Gielis curves, including self-intersecting and asymmetric curves, without increasing the overall complexity of the algorithm. Then, we show how complex curves of k-type can be constructed and how solutions to the Dirichlet problem for the Laplace equation on these complex domains can be derived using a semi-Fourier method. In all three …

An Integrated fuzzy Cells-classifier

2006

The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. In this paper a genetic algorithm is proposed to fuse the classification results due to different distance functions. The combination is based on the optimization of a vote strategy and it is applied to cells classification.

Ockham's Razor in Memetic Computing: Three Stage Optimal Memetic Exploration

2012

Memetic computing is a subject in computer science which considers complex structures as the combination of simple agents, memes, whose evolutionary interactions lead to intelligent structures capable of problem-solving. This paper focuses on memetic computing optimization algorithms and proposes a counter-tendency approach for algorithmic design. Research in the field tends to go in the direction of improving existing algorithms by combining different methods or through the formulation of more complicated structures. Contrary to this trend, we instead focus on simplicity, proposing a structurally simple algorithm with emphasis on processing only one solution at a time. The proposed algorit…