A search algorithm for global optimisation

S. Chen*, X. X. Wang, C. J. Harris

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

This paper investigates a global search optimisation technique, referred to as the repeated weighted boosting search. The proposed optimisation algorithm is extremely simple and easy to implement. Heuristic explanation is given for the global search capability of this technique. Comparison is made with the two better known and widely used global search techniques, known as the genetic algorithm and adaptive simulated annealing. The effectiveness of the proposed algorithm as a global optimiser is investigated through several examples.

Original languageEnglish
Pages (from-to)1122-1130
Number of pages9
JournalLecture Notes in Computer Science
Volume3611
Issue numberPART II
DOIs
Publication statusPublished - 24 Oct 2005

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Global Search
Global optimization
Global Optimization
Search Algorithm
Simulated annealing
Genetic algorithms
Boosting
Simulated Annealing
Optimization Techniques
Optimization Algorithm
Genetic Algorithm
Heuristics

Cite this

Chen, S., Wang, X. X., & Harris, C. J. (2005). A search algorithm for global optimisation. Lecture Notes in Computer Science, 3611(PART II), 1122-1130. https://doi.org/10.1007/11539117_152
Chen, S. ; Wang, X. X. ; Harris, C. J. / A search algorithm for global optimisation. In: Lecture Notes in Computer Science. 2005 ; Vol. 3611, No. PART II. pp. 1122-1130.
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Chen, S, Wang, XX & Harris, CJ 2005, 'A search algorithm for global optimisation', Lecture Notes in Computer Science, vol. 3611, no. PART II, pp. 1122-1130. https://doi.org/10.1007/11539117_152

A search algorithm for global optimisation. / Chen, S.; Wang, X. X.; Harris, C. J.

In: Lecture Notes in Computer Science, Vol. 3611, No. PART II, 24.10.2005, p. 1122-1130.

Research output: Contribution to journalArticle

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