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Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number
May 14-May 16
ISBN: 978-0-7695-3131-1
ASCII Text
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Dongshu Yan, Jintao Zhang, Bo Yu, Changtong Luo, Shaoliang Zhang, "A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number," Computer and Information Science, ACIS International Conference on, pp. 301-305, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), 2008.
 
 
BibTex
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@article{ 10.1109/ICIS.2008.38,
author = {Dongshu Yan and Jintao Zhang and Bo Yu and Changtong Luo and Shaoliang Zhang},
title = {A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number},
journal ={Computer and Information Science, ACIS International Conference on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3131-1},
pages = {301-305},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICIS.2008.38},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer and Information Science, ACIS International Conference on
TI - A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number
SN - 978-0-7695-3131-1
SP301
EP305
A1 - Dongshu Yan,
A1 - Jintao Zhang,
A1 - Bo Yu,
A1 - Changtong Luo,
A1 - Shaoliang Zhang,
PY - 2008
KW - genetic algorithm
KW - heuristics
KW - polynomial equations
KW - minimal multi-homogeneous Bezout number
VL - 0
JA - Computer and Information Science, ACIS International Conference on
ER -
 
Homotopy continuation is a most efficient numerical method for finding all isolated solutions of system of polynomial equations, and finding minimal multi-homogeneous Bezout number is a basic problem of homotopy continuation. This paper presents a problem-specific genetic algorithm for finding minimal multi-homogeneous Bezout number. The algorithm is easy to implement and easy to be parallelized for large scale problems. It can find the minimal multi-homogeneous Bezout number in probability 1. Numerical results indicate that the proposed algorithm is reliable and efficient. The algorithm offers a competitive alternative for minimal multi-homogeneous Bezout number problem. Meanwhile, it extends the application fields of genetic algorithms.
Index Terms:
genetic algorithm, heuristics, polynomial equations, minimal multi-homogeneous Bezout number
Citation:
Dongshu Yan, Jintao Zhang, Bo Yu, Changtong Luo, Shaoliang Zhang, "A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number," icis, pp.301-305, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), 2008
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