### Abstract

Cuckoo Search (CS) is a meta-heuristic optimization algorithm that is inspired by breeding strategy of some cuckoo species that involves laying of eggs in the nests of other host birds. Like other population based optimization algorithms, the initial positions of the population, in the case of CS are host nests, will influence the performance of the searching. Based on this fact, we believe that the CS algorithm can further be improved by strategically selecting the starting positions of the nests instead of the standard random selection. This work suggests the use of positions generated from the Centroidal Voronoi Tessellations (CVT) as the starting points for the nests. A CVT is a Voronoi tessellation of a set such that the generators of the Voronoi sets are simultaneously their centers of mass. The CVT will initially present the problem space in equally distributed manner. The performance of CS algorithm initialized using CVT is compared with those generated from the standard CS algorithm on several benchmark test functions. The results show that the initialization of CS algorithm using the CVT improves its performance especially for benchmark functions with high-dimensional input spaces.

Original language | English |
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Title of host publication | Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 |

Pages | 40-45 |

Number of pages | 6 |

DOIs | |

Publication status | Published - 2011 |

Event | 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 - Malacca Duration: 5 Dec 2011 → 8 Dec 2011 |

### Other

Other | 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 |
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City | Malacca |

Period | 5/12/11 → 8/12/11 |

### Fingerprint

### Keywords

- Centroidal Voronoi Tesselaations (CVT)
- Cuckoo Search (CS)
- Meta-heuristic
- Optimization algorithm

### ASJC Scopus subject areas

- Artificial Intelligence
- Information Systems

### Cite this

*Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011*(pp. 40-45). [6122077] https://doi.org/10.1109/HIS.2011.6122077

**Starting configuration of cuckoo search algorithm using centroidal voronoi tessellations.** / Shatnawi, Moaath; Nasrudin, Mohammad Faidzul.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011.*, 6122077, pp. 40-45, 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011, Malacca, 5/12/11. https://doi.org/10.1109/HIS.2011.6122077

}

TY - GEN

T1 - Starting configuration of cuckoo search algorithm using centroidal voronoi tessellations

AU - Shatnawi, Moaath

AU - Nasrudin, Mohammad Faidzul

PY - 2011

Y1 - 2011

N2 - Cuckoo Search (CS) is a meta-heuristic optimization algorithm that is inspired by breeding strategy of some cuckoo species that involves laying of eggs in the nests of other host birds. Like other population based optimization algorithms, the initial positions of the population, in the case of CS are host nests, will influence the performance of the searching. Based on this fact, we believe that the CS algorithm can further be improved by strategically selecting the starting positions of the nests instead of the standard random selection. This work suggests the use of positions generated from the Centroidal Voronoi Tessellations (CVT) as the starting points for the nests. A CVT is a Voronoi tessellation of a set such that the generators of the Voronoi sets are simultaneously their centers of mass. The CVT will initially present the problem space in equally distributed manner. The performance of CS algorithm initialized using CVT is compared with those generated from the standard CS algorithm on several benchmark test functions. The results show that the initialization of CS algorithm using the CVT improves its performance especially for benchmark functions with high-dimensional input spaces.

AB - Cuckoo Search (CS) is a meta-heuristic optimization algorithm that is inspired by breeding strategy of some cuckoo species that involves laying of eggs in the nests of other host birds. Like other population based optimization algorithms, the initial positions of the population, in the case of CS are host nests, will influence the performance of the searching. Based on this fact, we believe that the CS algorithm can further be improved by strategically selecting the starting positions of the nests instead of the standard random selection. This work suggests the use of positions generated from the Centroidal Voronoi Tessellations (CVT) as the starting points for the nests. A CVT is a Voronoi tessellation of a set such that the generators of the Voronoi sets are simultaneously their centers of mass. The CVT will initially present the problem space in equally distributed manner. The performance of CS algorithm initialized using CVT is compared with those generated from the standard CS algorithm on several benchmark test functions. The results show that the initialization of CS algorithm using the CVT improves its performance especially for benchmark functions with high-dimensional input spaces.

KW - Centroidal Voronoi Tesselaations (CVT)

KW - Cuckoo Search (CS)

KW - Meta-heuristic

KW - Optimization algorithm

UR - http://www.scopus.com/inward/record.url?scp=84856689695&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856689695&partnerID=8YFLogxK

U2 - 10.1109/HIS.2011.6122077

DO - 10.1109/HIS.2011.6122077

M3 - Conference contribution

AN - SCOPUS:84856689695

SN - 9781457721502

SP - 40

EP - 45

BT - Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011

ER -