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Hybrid genetic approach for 1-D bin packing problem

Hybrid genetic approach for 1-D bin packing problem This paper deals with the one-dimensional Bin Packing Problem (1-D BPP). Exact solution methods can only be used for very small instances, hence for real-world problems we have to focus on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to this problem, including Genetic Algorithms and Evolutionary Programming. In this paper, we propose a Hybrid Genetic Algorithm (HGA) to solve 1-D BPP. We compare our approach with algorithms given by Scholl et al., Alvim et al. and Kok-Hua et al. Then we discuss the performance of the approach. We show that giving at least the same performance on term of quality solution, our HGA approach outperforms these algorithms on term of computational time. This performance is due to new mechanisms of hybridisation of genetic algorithms and local search. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Services Operations and Informatics Inderscience Publishers

Hybrid genetic approach for 1-D bin packing problem

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1741-539X
eISSN
1741-5403
DOI
10.1504/IJSOI.2011.038315
Publisher site
See Article on Publisher Site

Abstract

This paper deals with the one-dimensional Bin Packing Problem (1-D BPP). Exact solution methods can only be used for very small instances, hence for real-world problems we have to focus on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to this problem, including Genetic Algorithms and Evolutionary Programming. In this paper, we propose a Hybrid Genetic Algorithm (HGA) to solve 1-D BPP. We compare our approach with algorithms given by Scholl et al., Alvim et al. and Kok-Hua et al. Then we discuss the performance of the approach. We show that giving at least the same performance on term of quality solution, our HGA approach outperforms these algorithms on term of computational time. This performance is due to new mechanisms of hybridisation of genetic algorithms and local search.

Journal

International Journal of Services Operations and Informatics – Inderscience Publishers

Published: Jan 1, 2011

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