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The quadratic assignment problem: metaheuristic optimization using HC12 algorithm

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F19%3APU132650" target="_blank" >RIV/00216305:26210/19:PU132650 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/citation.cfm?doid=3319619.3322088" target="_blank" >https://dl.acm.org/citation.cfm?doid=3319619.3322088</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3319619.3322088" target="_blank" >10.1145/3319619.3322088</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The quadratic assignment problem: metaheuristic optimization using HC12 algorithm

  • Original language description

    The Quadratic Assignment Problem (QAP) is a classical NP-hard combinatorial optimization problem. In the paper will be presented suitable metaheuristic algorithm HC12. The algorithm is population based and uses a massive parallel search of the binary space which represents the solution space of the QAP. The presented implementation of the metaheuristic HC12 utilizes the latest GPU CUDA platform. The results are presented on standard test problems from the QAP library.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LTC18053" target="_blank" >LTC18053: Advanced Methods of Nature-Inspired Optimisation and HPC Implementation for the Real-Life Applications</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Companion

  • ISBN

    978-1-4503-6748-6

  • ISSN

  • e-ISSN

  • Number of pages

    2

  • Pages from-to

    153-154

  • Publisher name

    ACM

  • Place of publication

    New York, NY, USA

  • Event location

    Praha

  • Event date

    Jul 13, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article