Free Search Applied to Large Constraint Optimisation Problem

Research output: Chapter in Book/Report/Published conference proceedingChapterpeer-review

Abstract

The article presents experimental results achieved by Free Search on optimisation of 100 dimensional version of so called bump test problem. Free Search is adaptive heuristic algorithm. It operates on a set of solutions called population and it can be classi?ed as population-based method. It gradually modi?es a set of solutions according to the prior de?ned objective function. The aim of the study is to identify how Free Search can diverge from one starting location in the middle of the search space in comparison to start from random locations in the middle of the search space and start from stochastic locations uniformly generated within the whole search space. The results achieved form the experiments with above initialisation strategies are presented. A discussion focuses on the ability of Free Search to diverge from one location if the process stagnates in local trap during the search. The article presents, also, the values of the variables for the best achieved results, which could be used for comparison to other methods and further investigation.
Original languageEnglish
Title of host publicationLarge-Scale Scientific Computing
Place of PublicationBulgaria
PublisherSpringer
Pages593-600
Number of pages8
ISBN (Print)978 3 540 78825 6
Publication statusPublished - 1 Jun 2007

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