Evolving feasible linear ordering problem solutions

Authors:
Pavel Krömer;Václav Snášel;Jan Platoš
Affiliations:
University of Ostrava, Ostrava -- Poruba, Czech Republic;University of Ostrava, Ostrava -- Poruba, Czech Republic;University of Ostrava, Ostrava -- Poruba, Czech Republic
Venue:
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Year:
2008

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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.