Title :
Solving one-billion-bit Noisy OneMax problem using Estimation Distribution Algorithm with Arithmetic Coding
Author :
Suwannik, Worasait ; Chongstitvatana, Prabhas
Author_Institution :
Dept. of Comput. Sci., Kasetsart Univ., Bangkok
Abstract :
This paper presents an algorithm which combines estimation distribution algorithm with a chromosome compression scheme to solve large scale noisy OneMax problem. The search space reduction resulted from chromosome compression enables the algorithm to solve a one-billion-bit problem. Arithmetic coding represents a compressed binary string with two real numbers. Using this representation, a model of highly fit individuals can be constructed. This model can be used to evolve the solution in the manner of estimation distribution algorithm. The experimental result shows that the algorithm can solve billion-bit Noisy OneMax problem in about 34 hours using a normal PC-class computer.
Keywords :
arithmetic codes; binary codes; data compression; PC-class computer; arithmetic coding; chromosome compression scheme; estimation distribution algorithm; large scale noisy OneMax problem; one-billion-bit noisy OneMax problem; Arithmetic; Biological cells; Compression algorithms; Computer science; Encoding; Gaussian distribution; Genetic algorithms; Large-scale systems; Partitioning algorithms;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4630949
