A Percentile Transition Ranking Algorithm Applied to Knapsack Problem

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18 Scopus citations

Abstract

The binarization of Swarm Intelligence continuous 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 Percentile Transition Ranking Algorithm (PTRA). PTRA uses the percentile concept as a binarization mechanism. In particular we will apply this mechanism to the Cuckoo Search metaheuristic to solve the set multidimensional Knapsack problem (MKP). We provide necessary experiments to investigate the role of key ingredients of the algorithm. Finally to demonstrate the efficiency of our proposal, we solve Knapsack benchmark instances of the literature. These instances show PTRA competes with the state-of-the-art algorithms.

Original languageEnglish
Title of host publicationApplied Computational Intelligence and Mathematical Methods - Computational Methods in Systems and Software 2017
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Pages126-138
Number of pages13
ISBN (Print)9783319676203
DOIs
StatePublished - 1 Jan 2018
EventInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017 - Vsetin, Czech Republic
Duration: 12 Sep 201714 Sep 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume662
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017
CountryCzech Republic
CityVsetin
Period12/09/1714/09/17

Keywords

  • Combinatorial optimization
  • Metaheuristics
  • Multidimensional knapsack problem

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