Title :
A study on performance of MOGA and HLCGA for the Linear Ordering Problem
Author :
Pavel Kromer;Jan Platos;Vaclav Snasel
Author_Institution :
Department of Computer Science, Faculty of Electrical Engineering and Computer Science, V?B - Technical University of Ostrava, 17. listopadu 15, 708 33 Poruba, Czech Republic
fDate :
6/1/2008 12:00:00 AM
Abstract :
Linear Ordering Problem (LOP) is a well know optimization problem attractive for its complexity (it is a NP-hard problem), rich collection of testing data and variety of real world applications. In this paper, we investigate the usage and performance of two variants of Genetic Algorithms - Mutation Only Genetic Algorithms and Higher Level Chromosome Genetic Algorithms - on the Linear Ordering Problem. Both methods are tested and evaluated on a collection of real world and artificial LOP instances.
Keywords :
"Genetic algorithms","Optimization methods","Biological cells","Computer science","Benchmark testing","Evolutionary computation","Encoding","NP-hard problem","Job shop scheduling","Libraries"
Conference_Titel :
Soft Computing in Industrial Applications, 2008. SMCia ´08. IEEE Conference on
Print_ISBN :
978-1-4244-3782-5
DOI :
10.1109/SMCIA.2008.5045997
