Free Search—a comparative analysis

Kalin Penev, Guy Littlefair

Research output: Contribution to journalArticle


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

Fingerprint Dive into the research topics of 'Free Search—a comparative analysis'. Together they form a unique fingerprint.

  • Cite this