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A Generalized Markov-Chain Modelling Approach to (1,lambda)-ES Linear Optimization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00441534" target="_blank" >RIV/67985807:_____/14:00441534 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-10762-2_89" target="_blank" >http://dx.doi.org/10.1007/978-3-319-10762-2_89</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-10762-2_89" target="_blank" >10.1007/978-3-319-10762-2_89</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Generalized Markov-Chain Modelling Approach to (1,lambda)-ES Linear Optimization

  • Original language description

    Several recent publications investigated Markov-chain modelling of linear optimization by a (1, lambda)-ES, considering both unconstrained and linearly constrained optimization, and both constant and varying step size. All of them assume normality of theinvolved random steps, and while this is consistent with a black-box scenario, information on the function to be optimized (e.g. separability) may be exploited by the use of another distribution. The objective of our contribution is to complement previous studies realized with normal steps, and to give sufficient conditions on the distribution of the random steps for the success of a constant step-size (1, lambda)-ES on the simple problem of a linear function with a linear constraint. The decompositionof a multidimensional distribution into its marginals and the copula combining them is applied to the new distributional assumptions, particular attention being paid to distributions with Archimedean copulas.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2014

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Parallel Problem Solving from Nature - PPSN XIII

  • ISBN

    978-3-319-10761-5

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    902-911

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Ljubljana

  • Event date

    Sep 13, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article