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2021 | OriginalPaper | Chapter

Increase Driver’s Comfort Using Multi-population Evolutionary Algorithm

Authors : Szymon Tengler, Kornel Warwas

Published in: Recent Challenges in Intelligent Information and Database Systems

Publisher: Springer Singapore

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Abstract

An application of own algorithm for reduction optimization calculation time is presented in the paper. The algorithm is called Distributed Multi-Population Evolutionary Algorithm and uses a genetic algorithm with real-coded genes in the chromosome. The client-server architecture was used for processing lots of populations with a simultaneous data exchange between the populations. Each generation consists of standard genetic operators: a natural selection, one-point crossing, uniform mutation and a data exchange within the computational units. This method was used for selecting values of damping coefficients of a driver’s seat sub-assembly to improve driving comfort. Numerical results of a vehicle driving with different variants of velocity and obstacles are presented in the paper.

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Metadata
Title
Increase Driver’s Comfort Using Multi-population Evolutionary Algorithm
Authors
Szymon Tengler
Kornel Warwas
Copyright Year
2021
Publisher
Springer Singapore
Book
Recent Challenges in Intelligent Information and Database Systems

Print ISBN: 978-981-16-1684-6

Electronic ISBN: 978-981-16-1685-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-1685-3_29

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