A Modified Differential Evolution With Distance-based Selection for Continuous Optimization in Presence of Noise

A Modified Differential Evolution With Distance-based Selection for Continuous Optimization in Presence of Noise

The performance of evolutionary algorithms (EAs), suitable for optimization on static functional landscapes, usually degrade in presence of noises with different statistical features. In this paper, we present a simple variant of the differential evolution (DE) algorithm, one of the most competitive...

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Bibliographic Details
Main Authors: Arka Ghosh, Swagatam Das, Rammohan Mallipeddi, Asit Kumar Das, Subhransu Sekhar Dash
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Differential evolution
noisy optimization
selection
gaussian noise
poisson noise
Online Access:https://ieeexplore.ieee.org/document/8110609/

Internet

https://ieeexplore.ieee.org/document/8110609/

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