Conference Proceedings

Metaheuristic Algorithm Similarity Analysis Based on Performance Metric Mapping of Fractional Ranking

Yong-Wei Zhang, Saman K Halgamuge

2018 IEEE 9TH INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION FOR SUSTAINABILITY (ICIAFS' 2018) | IEEE | Published : 2018

Abstract

Although the diversity of metaheuristic algorithms has been frequently highlighted, the similarity of these algorithms is not studied comprehensively. This work studies the similarity of metahruristic algorithms from their performance perspective captured in a newly proposed fractional ranking method, which can map comprehensive performance measures into a scalar framework. The fractional ranking data is clustered using a k-medoids clustering to find similarities between algorithms. Results show that the proposed similarity analysis scheme reveals a new perspective of metaheuristic algorithms.

University of Melbourne Researchers

Grants

Awarded by Jiangsu Government Fellowship for Overseas Research Studies


Funding Acknowledgements

This work is partially supported by the Jiangsu Government Fellowship for Overseas Research Studies (JS-2015-200) awarded to Dr. Yong-Wei Zhang.