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Accelerating a Flow Shop Algorithm on the GPU

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00181903" target="_blank" >RIV/68407700:21230/11:00181903 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Accelerating a Flow Shop Algorithm on the GPU

  • Original language description

    We present a GPGPU (General-Purpose computing on Graphics Processing Units) based approach to combinatorial problems, specifically to the permutation flow shop scheduling problem. Presented genetic algorithm uses the homogeneous computing model in orderto maximize the algorithm performance. The algorithm is based on work presented by Pospichal et al. In our paper, we suggest several improvements (e.g. another mechanism for individuals migration, more efficient problem representation) allowing to applythis algorithm on a wider group of NP-hard combinatorial problems. Our experimental results show significant speedup with respect to the sequential algorithm version.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GPP103%2F10%2FP401" target="_blank" >GPP103/10/P401: Optimization Algorithms for the Project Scheduling Problem</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

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