Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

An improved genetic algorithm for solving packing problem

Authors
Zhi-yan Li
Corresponding Author
Zhi-yan Li
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.361How to use a DOI?
Keywords
Bin-Packing Problem; Genetic Algorithm; Best Fit Decrease; Combination Optimization
Abstract

Targeted at solving slow rate of convergence in the current genetic algorithm, an improved genetic algorithm is put forward in the article. The current genetic algorithm is improved by adding the best fit decrease algorithm to generate individuals into the initial population, conversing the preservation strategy and fitness of the optimum individual. To verify the validness of the algorithm, simulation experiments are designed. And the result of these experiments shows that the improved algorithm has the bigger probability to find the optimal solution and faster solution speed.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.361How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhi-yan Li
PY  - 2016/03
DA  - 2016/03
TI  - An improved genetic algorithm for solving packing problem
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1815
EP  - 1820
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.361
DO  - 10.2991/icmmct-16.2016.361
ID  - Li2016/03
ER  -