Free Search—a comparative analysis

Kalin Penev, Guy Littlefair

    Research output: Contribution to journalArticlepeer-review


    The article presents a novel population-based optimisation method, called Free Search (FS). Essential peculiarities of the new method are introduced. The aim of the study is to identify how robust is Free Search. Explored and compared are four different population-based optimisation methods, namely Genetic Algorithm (in real coded BLX-α modification), Particle Swarm Optimisation, Differential Evolution and Free Search. They are applied to five non-linear, heterogeneous, numerical, optimisation problems. The achieved results suggest that Free Search has stable robust behaviour on explored tests; FS can cope with heterogeneous optimisation problems; FS is applicable to unknown (black-box) real-world optimisation tasks.
    Original languageEnglish
    Pages (from-to)173-193
    Number of pages20
    JournalInformation Sciences
    Issue number1-2
    Publication statusPublished - 9 Jun 2005


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