Quick Combinatorial Artificial Bee Colony -qCABC- Optimization Algorithm for TSP

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dc.contributor.author Görkemli, Beyza
dc.contributor.author Karaboga, Dervis
dc.date.accessioned 2013-12-19T14:32:37Z
dc.date.accessioned 2015-11-19T12:50:22Z
dc.date.available 2013-12-19T14:32:37Z
dc.date.available 2015-11-19T12:50:22Z
dc.date.issued 2013-12-19
dc.identifier.uri http://dspace.epoka.edu.al/handle/1/849
dc.description.abstract Combinatorial Artificial Bee Colony Algorithm (CABC) is a new version of Artificial Bee Colony (ABC) to solve combinatorial type optimization problems and quick Artificial Bee Colony (qABC) algorithm is an improved version of ABC in which the onlooker bees behavior is modeled in more detailed way. Studies showed that qABC algorithm improves the convergence performance of standard ABC on numerical optimization. In this paper, to see the performance of this new modeling way of onlookers' behavior on combinatorial optimization, we apply the qABC idea to CABC and name this new algorithm as quick CABC (qCABC). qCABC is tested on Traveling Salesman Problem and simulation results show that qCABC algorithm improves the convergence and final performance of CABC. en_US
dc.language.iso en en_US
dc.relation.ispartofseries paper_43;
dc.subject combinatorial optimization en_US
dc.subject swarm intelligence en_US
dc.subject artificial bee colony en_US
dc.title Quick Combinatorial Artificial Bee Colony -qCABC- Optimization Algorithm for TSP en_US
dc.type Book chapter en_US


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  • ISCIM 2013
    2nd International Symposium on Computing in Informatics and Mathematics

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