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Combinatorial optimization with distributed genetic algorithms

Andrej Čopar (2012) Combinatorial optimization with distributed genetic algorithms. EngD thesis.

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    With combinatorial optimization we try to find good solutions for many computationaly difficult problems. For this type of problems we often use metaheuristics such as genetic algorithms. We describe complexity classes NP and P and relation between them. We present genetic algorithms with different parallelization models. Main part consists of distributed genetic algorithm implementation using client-server schema and island model. We develop communications protocol and graphical user interface. We analyze several algorithm and distribution parameters and test our implementation using traveling salesman problem collection.

    Item Type: Thesis (EngD thesis)
    Keywords: combinatorial optimization, NP complete problems, genetic algorithms, traveling salesman problem, distributed computing
    Number of Pages: 48
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    prof. dr. Marko Robnik Šikonja276Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=00009476948)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 1796
    Date Deposited: 12 Sep 2012 10:14
    Last Modified: 30 Oct 2012 09:20
    URI: http://eprints.fri.uni-lj.si/id/eprint/1796

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