An improved genetic algorithm for solving packing problem
- 10.2991/icmmct-16.2016.361How to use a DOI?
- Bin-Packing Problem; Genetic Algorithm; Best Fit Decrease; Combination Optimization
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.
- © 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 -