Finding multiple first order saddle points using a valley adaptive clearing genetic algorithm

Authors:
Mostafa M. H. Ellabaan;Yew Soon Ong;Meng Hiot Lim;Kuo Jer-Lai
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore
Venue:
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Year:
2009

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Abstract

First order saddle points have important applications in different fields of science and engineering. Some of their interesting applications include estimation of chemical reaction rate, image segmentation, path-planning and robotics navigation. Finding such points using evolutionary algorithms is a field that remains yet to be well investigated. In this paper, we present an evolutionary algorithm that is designed for finding multiple saddle points. In contrast to earlier work (1], we propose a new fitness function that favors 1st order saddle points or transition states. In particular, a valley adaptive clearing multi-modal evolutionary optimization approach is proposed to locate and archive multiple solutions by directing the search towards unexplored regions of the search space [2]. Experimental results on benchmark functions and the Lennard Jones Potential are presented to demonstrate the efficacy of the proposed algorithm in locating multiple 1st order saddle points.