An improved genetic algorithm for solving packing problem

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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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  -