Matrix-Chain Multiplication Problem using Genetic Algorithm

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Published: Nov 12, 2018
Keywords:
tree encoding, matrix-chain multiplication, genetic algorithm

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Soontharee Koompairojn*
School of Computer Science, University of Central Florida, Orlando, USA
Minh Le
School of Computer Science, University of Central Florida, Orlando, USA

Abstract

Tree encoding has been studied for the genetic algorithm on artificial intelligence such as sequence induction, automatic programming, machine learning, and pattern recognition [5]. This paper also presents the tree encoding for the genetic algorithm in solving the matrix-chain multiplication, which is in the form A1 A2 A3 … AN where Ai is a matrix. Tress are generated as the way the matrices are fully parenthesized. Then crossover and mutation are applied. The fitness value is calculated and stored at the root of the tree.


Keywords:  tree encoding, matrix-chain multiplication, genetic algorithm


Corresponding author: E-mail: soonthar@cs.ucf.edu

Article Details

How to Cite
Koompairojn*, S., & Le, M. (2018). Matrix-Chain Multiplication Problem using Genetic Algorithm. CURRENT APPLIED SCIENCE AND TECHNOLOGY, 5(1), 255–265. retrieved from https://li01.tci-thaijo.org/index.php/cast/article/view/160799
Issue
Vol. 5 No. 1 (2005)
Section
Original Research Articles

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References

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[4] Hu, T.C., and Shing, M.T. 1982 Computation of Matrix Chain Products Part I. SIAM J. computing, 11(2).
[5] Koza, J.R. 1989 Hierarchical Genetic Algorithms Operating on Populations of Computer Programs. International Joint Conference on Artificial Intelligence.