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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-way Test Suite Generation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00308979" target="_blank" >RIV/68407700:21230/17:00308979 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.sciencedirect.com/science/article/pii/S0020025517305820" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0020025517305820</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ins.2017.03.007" target="_blank" >10.1016/j.ins.2017.03.007</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-way Test Suite Generation

  • Original language description

    Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. Hyper-heuristics provide an alternative methodology to meta-heuristics which permit adaptive selection and/or generation of meta-heuristics automatically during the search process. This paper describes our experience with four hyper-heuristic selection and acceptance mechanisms namely Exponential Monte Carlo with counter (EMCQ), Choice Function (CF), Improvement Selection Rules (ISR), and newly developed Fuzzy Inference Selection (FIS), using the t-way test generation problem as a case study. Based on the experimental results, we offer insights on why each strategy differs in terms of its performance.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • 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

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Information Sciences

  • ISSN

    0020-0255

  • e-ISSN

    1872-6291

  • Volume of the periodical

    399

  • Issue of the periodical within the volume

    August

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    33

  • Pages from-to

    121-153

  • UT code for WoS article

    000400203900008

  • EID of the result in the Scopus database

    2-s2.0-85015674025