A percentile transition ranking algorithm applied to binarization of continuous swarm intelligence metaheuristics

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19 Scopus citations

Abstract

The binarization of continuous swarm-intelligence metaheuristics is an area of great interest in operational research. This interest is mainly due to the application of binarized metaheuristics to combinatorial problems. In this article we propose a general binarization algorithm called Percentil Transition Ranking Algorithm (PTRA). PTRA uses the percentile concept as a binarization mechanism. In particular we apply this mechanism to the Cuckoo Search metaheuristic to solve the Set Covering Problem (SCP). We provide necessary experiments to investigate the role of key ingredients of the algorithm. Finally to demonstrate the efficiency of our proposal, Set Covering benchmark instances of the literature show that PTRA competes with the state-of-the-art algorithms.

Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining - Proceedings of the 3rd International Conference on Soft Computing and Data Mining SCDM 2018
EditorsJemal H. Abawajy, Rozaida Ghazali, Mustafa Mat Deris, Nazri Mohd Nawi
PublisherSpringer Verlag
Pages3-13
Number of pages11
ISBN (Print)9783319725499
DOIs
StatePublished - 1 Jan 2018
Event3rd International Conference on Soft Computing and Data Mining, SCDM 2018 - Johor, Malaysia
Duration: 6 Feb 20188 Feb 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume700
ISSN (Print)2194-5357

Conference

Conference3rd International Conference on Soft Computing and Data Mining, SCDM 2018
CountryMalaysia
CityJohor
Period6/02/188/02/18

Keywords

  • Binary metaheuristics
  • Combinatorial optimization
  • Percentile ranking
  • Set covering problem

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