Runtime analysis of evolutionary programming based on Cauchy mutation

Han Huang; Zhifeng Hao; Zhaoquan Cai; Yifan Zhu

doi:10.1007/978-3-642-17563-3_27

Runtime analysis of evolutionary programming based on Cauchy mutation

Han Huang
, Zhifeng Hao
, Zhaoquan Cai
, Yifan Zhu

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

This paper puts forward a brief runtime analysis of an evolutionary programming (EP) which is one of the most important continuous optimization evolutionary algorithms. A theoretical framework of runtime analysis is proposed by modeling EP as an absorbing Markov process. The framework is used to study the runtime of a classical EP algorithm named as EP with Cauchy mutation (FEP). It is proved that the runtime of FEP can be less than a polynomial of n if the Lebesgue measure of optimal solution set is more than an exponential form of 2. Moreover, the runtime analysis result can be used to explain the performance of EP based on Cauchy mutation. © 2010 Springer-Verlag.

Original language	English
Title of host publication	Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings
Pages	222-229
Volume	6466 LNCS
DOIs	https://doi.org/10.1007/978-3-642-17563-3_27
Publication status	Published - 2010
Externally published	Yes
Event	1st Swarm, Evolutionary and Memetic Computing Conference, SEMCCO 2010 - Chennai, India Duration: 16 Dec 2010 → 18 Dec 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6466 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st Swarm, Evolutionary and Memetic Computing Conference, SEMCCO 2010
Place	India
City	Chennai
Period	16/12/10 → 18/12/10

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

National Natural Science Foundation of China (61003066,61070033), Doctoral Program of the Ministry of Education (20090172120035), Natural Science Foundation of Guangdong Province (9151008901000165, 10151601501000015), Key Technology Research and Development Programs of Guangdong Province (2009B010800026) and Fundamental Research Funds for the Central Universities, SCUT(2009ZM0052), Key Technology Research and Development Programs of Huizhou (2009G024) and Special Fund Project of Huizhou Modern Information Services.

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10.1007/978-3-642-17563-3_27

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Huang, H., Hao, Z., Cai, Z., & Zhu, Y. (2010). Runtime analysis of evolutionary programming based on Cauchy mutation. In Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings (Vol. 6466 LNCS, pp. 222-229). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6466 LNCS). https://doi.org/10.1007/978-3-642-17563-3_27

Huang, Han ; Hao, Zhifeng ; Cai, Zhaoquan et al. / Runtime analysis of evolutionary programming based on Cauchy mutation. Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings. Vol. 6466 LNCS 2010. pp. 222-229 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Runtime analysis of evolutionary programming based on Cauchy mutation",

abstract = "This paper puts forward a brief runtime analysis of an evolutionary programming (EP) which is one of the most important continuous optimization evolutionary algorithms. A theoretical framework of runtime analysis is proposed by modeling EP as an absorbing Markov process. The framework is used to study the runtime of a classical EP algorithm named as EP with Cauchy mutation (FEP). It is proved that the runtime of FEP can be less than a polynomial of n if the Lebesgue measure of optimal solution set is more than an exponential form of 2. Moreover, the runtime analysis result can be used to explain the performance of EP based on Cauchy mutation. {\textcopyright} 2010 Springer-Verlag.",

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Huang, H, Hao, Z, Cai, Z & Zhu, Y 2010, Runtime analysis of evolutionary programming based on Cauchy mutation. in Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings. vol. 6466 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6466 LNCS, pp. 222-229, 1st Swarm, Evolutionary and Memetic Computing Conference, SEMCCO 2010, Chennai, India, 16/12/10. https://doi.org/10.1007/978-3-642-17563-3_27

Runtime analysis of evolutionary programming based on Cauchy mutation. / Huang, Han; Hao, Zhifeng; Cai, Zhaoquan et al.
Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings. Vol. 6466 LNCS 2010. p. 222-229 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6466 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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Huang H, Hao Z, Cai Z, Zhu Y. Runtime analysis of evolutionary programming based on Cauchy mutation. In Swarm, Evolutionary, and Memetic Computing - First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Proceedings. Vol. 6466 LNCS. 2010. p. 222-229. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-17563-3_27

Runtime analysis of evolutionary programming based on Cauchy mutation

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