A search algorithm for global optimisation

S. Chen; X. X. Wang; C. J. Harris

doi:10.1007/11539117_152

A search algorithm for global optimisation

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

^*Corresponding author for this work

Mathematics

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	1122-1130
Number of pages	9
Journal	Lecture Notes in Computer Science
Volume	3611
Issue number	PART II
DOIs	https://doi.org/10.1007/11539117_152
Publication status	Published - 24 Oct 2005

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title = "A search algorithm for global optimisation",

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.",

author = "S. Chen and Wang, {X. X.} and Harris, {C. J.}",

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AU - Harris, C. J.

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N2 - 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.

AB - 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.

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UR - https://link.springer.com/chapter/10.1007/11539117_152

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JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

IS - PART II

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A search algorithm for global optimisation

Abstract

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