A novel genetic algorithm for the Layout Optimization Problem

Yi Chun Xu*, Ren Bin Xiao, Martyn Amos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Citations (Scopus)

Abstract

In this paper we present a new algorithm for the Layout Optimization Problem: this concerns the placement of circular, weighted objects inside a circular container, the two objectives being to minimize imbalance of mass and to minimize the radius of the container. This problem carries real practical significance in industrial applications (such as the design of satellites), as well as being of significant theoretical interest. We present a genetic algorithm solution and compare it with two existing nature-inspired methods, one of which is the best published algorithm for this problem. Experimental results show that our approach out-performs these existing methods in terms of both solution quality and execution time.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
PublisherIEEE
Pages3938-3943
Number of pages6
ISBN (Print)9781424413409
DOIs
Publication statusPublished - 7 Jan 2008
Externally publishedYes
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: 25 Sep 200728 Sep 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
CountrySingapore
Period25/09/0728/09/07

Fingerprint Dive into the research topics of 'A novel genetic algorithm for the Layout Optimization Problem'. Together they form a unique fingerprint.

Cite this