Mathematical analysis of schema survival for genetic algorithms having dual mutation-Reference-Cited by-同舟云学术

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Mathematical analysis of schema survival for genetic algorithms having dual mutation

Published:2017-06-01 Issue:6 Volume:22 Page:1763-1771
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Mishra Apoorva^ORCID,Shukla Anupam

Funder

Department of Electronics and Information Technology, Ministry of Communication and Information Technology, Government of India

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s00500-017-2650-3/fulltext.html

Reference16 articles.

1. Banerjee A (2013) A novel probabilistically-guided context-sensitive crossover operator for clustering. Swarm Evol Comput. doi: 10.1016/j.swevo.2013.05.007

2. Basagoiti MBR, Rodriguez IRV (2016) A modified genetic algorithm applied to the elevator dispatching problem. Soft Comput. doi: 10.1007/s00500-015-1718-1

3. Faraji R, Naji HR (2014) An efficient crossover architecture for hardware parallel implementation of genetic algorithm. Neurocomputing. doi: 10.1016/j.neucom.2013.08.035

4. Goldberg D (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading

5. Hsu C, Cho H (2015) A genetic algorithm for the maximum edge-disjoint paths problem. Neurocomputing. doi: 10.1016/j.neucom.2012.10.046

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