A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems

Muhammad Marwan Muhammad Fuad

doi:10.1007/978-3-642-53917-6_35

A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems

Muhammad Marwan Muhammad Fuad

University of Tromsø

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

Metaheuristics are probabilistic optimization algorithms which are applicable to a wide range of optimization problems. Bio-inspired, also called nature-inspired, optimization algorithms are the most widely-known metaheuristics. The general scheme of bio-inspired algorithms consists in an initial stage of randomly generated solutions which evolve through search operations, for several generations, towards an optimal value of the fitness function of the optimization problem at hand. Such a scenario requires repeated evaluation of the fitness function. While in some applications each evaluation will not take more than a fraction of a second, in others, mainly those encountered in data mining, each evaluation may take up several minutes, hours, or even more. This category of optimization problems is called expensive optimization. Such cases require a certain modification of the above scheme. In this paper we present a new method for handling expensive optimization problems. This method can be applied with different population-based bio-inspired optimization algorithms. Although the proposed method is independent of the application to which it is applied, we experiment it on a data mining task.

Original language	English
Title of host publication	Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings
Editors	Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang
Publisher	Springer
Pages	396-403
Number of pages	8
Edition	PART 2
ISBN (Print)	9783642539169
DOIs	https://doi.org/10.1007/978-3-642-53917-6_35
Publication status	Published - 1 Dec 2013
Externally published	Yes
Event	9th International Conference on Advanced Data Mining and Applications, ADMA 2013 - Hangzhou, China Duration: 14 Dec 2013 → 16 Dec 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8347 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on Advanced Data Mining and Applications, ADMA 2013
Country/Territory	China
City	Hangzhou
Period	14/12/13 → 16/12/13

Keywords

Bio-inspired Optimization
Differential Evolution
Expensive Optimization
Genetic Algorithms
Metaheuristics
Optimization Applications in Data Mining

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-53917-6_35

Cite this

Fuad, M. M. M. (2013). A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems. In H. Motoda, Z. Wu, L. Cao, O. Zaiane, M. Yao, & W. Wang (Eds.), Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings (PART 2 ed., pp. 396-403). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8347 LNAI, No. PART 2). Springer. https://doi.org/10.1007/978-3-642-53917-6_35

A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems. / Fuad, Muhammad Marwan Muhammad.
Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings. ed. / Hiroshi Motoda; Zhaohui Wu; Longbing Cao; Osmar Zaiane; Min Yao; Wei Wang. PART 2. ed. Springer, 2013. p. 396-403 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8347 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Fuad, MMM 2013, A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems. in H Motoda, Z Wu, L Cao, O Zaiane, M Yao & W Wang (eds), Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8347 LNAI, Springer, pp. 396-403, 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, Hangzhou, China, 14/12/13. https://doi.org/10.1007/978-3-642-53917-6_35

Fuad MMM. A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems. In Motoda H, Wu Z, Cao L, Zaiane O, Yao M, Wang W, editors, Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings. PART 2 ed. Springer. 2013. p. 396-403. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-53917-6_35

Fuad, Muhammad Marwan Muhammad. / A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems. Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings. editor / Hiroshi Motoda ; Zhaohui Wu ; Longbing Cao ; Osmar Zaiane ; Min Yao ; Wei Wang. PART 2. ed. Springer, 2013. pp. 396-403 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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A pre-initialization stage of population-based bio-inspired metaheuristics for handling expensive optimization problems

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