Research on a Weight Coefficient Cluster Covering Multi-objective Genetic Algorithm

DOI

10.2991/icetms.2013.400How to use a DOI?

Keywords

genetic algorithm; multi-objective optimization; operator; pareto solution; cluster covering.

Abstract

A novel weight coefficient cluster covering genetic algorithm for multi-objective optimization is discussed. First, the principle and key technologies of the algorithm are presented, including cluster covering, weight coefficients, computing patterns, accurate decoding and fuzzy decoding. Then, its workflow is analyzed. An example is used to test the algorithm and the influence of algorithm parameters on computing results is also analyzed. The results show that the algorithm is effective. The algorithm can adopt several computing patterns. Both accurate decoding and fuzzy decoding have good astringency and diversity distribution.

Copyright

© 2013, 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  - Yan Cao
AU  - Niping Gao
AU  - Sen Cao
PY  - 2013/06
DA  - 2013/06
TI  - Research on a Weight Coefficient Cluster Covering Multi-objective Genetic Algorithm
BT  - Proceedings of the 2013 Conference on Education Technology and Management Science (ICETMS 2013)
PB  - Atlantis Press
SP  - 1492
EP  - 1495
SN  - 1951-6851
UR  - https://doi.org/10.2991/icetms.2013.400
DO  - 10.2991/icetms.2013.400
ID  - Cao2013/06
ER  -