GENETIC ALGORITHM VERSUS ANT COLONY OPTIMIZATION ALGORITHM - Comparison of Performances in Robot Path Planning Application

Nohaidda Binti Sariff, Norlida Buniyamin

2010

Abstract

This paper presents the results of a research that uses a simulation approach to compare the effectiveness and efficiency of two path planning algorithms. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) Algorithm for Robot Path Planning (RPP) were tested in a global static environment. Both algorithms were applied within a global map that provides feasible nodes from start point to goal. Performances between both algorithms were compared and evaluated in terms of computational efficiency by measuring the speed and number of iterations, accuracy of solution, solution variation and convergence behavior.

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Paper Citation


in Harvard Style

Binti Sariff N. and Buniyamin N. (2010). GENETIC ALGORITHM VERSUS ANT COLONY OPTIMIZATION ALGORITHM - Comparison of Performances in Robot Path Planning Application . In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8425-00-3, pages 125-132. DOI: 10.5220/0002892901250132


in Bibtex Style

@conference{icinco10,
author={Nohaidda Binti Sariff and Norlida Buniyamin},
title={GENETIC ALGORITHM VERSUS ANT COLONY OPTIMIZATION ALGORITHM - Comparison of Performances in Robot Path Planning Application},
booktitle={Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2010},
pages={125-132},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002892901250132},
isbn={978-989-8425-00-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - GENETIC ALGORITHM VERSUS ANT COLONY OPTIMIZATION ALGORITHM - Comparison of Performances in Robot Path Planning Application
SN - 978-989-8425-00-3
AU - Binti Sariff N.
AU - Buniyamin N.
PY - 2010
SP - 125
EP - 132
DO - 10.5220/0002892901250132