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

Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA

Volumn , Issue , 2009, Pages 457-462

  Ellabaan, Mostafa M H ^a   Ong, Yew Soon ^a   Lim, Meng Hiot ^b   Jer Lai, Kuo ^c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Evolutionary optimization; First orders saddle points; Robotics navagation; Transition states

Indexed keywords

BENCHMARK FUNCTIONS; EVOLUTIONARY OPTIMIZATIONS; FIRST ORDER; FITNESS FUNCTIONS; LENNARD-JONES POTENTIAL; MULTI-MODAL; MULTIPLE FIRST-ORDER; MULTIPLE SADDLE POINTS; MULTIPLE SOLUTIONS; PATH-PLANNING; SADDLE POINT; SCIENCE AND ENGINEERING; SEARCH SPACES; TRANSITION STATE;

ADAPTIVE ALGORITHMS; CHEMICAL REACTIONS; FUNCTION EVALUATION; IMAGE SEGMENTATION; LANDFORMS; OPTIMIZATION; REACTION RATES; ROBOT PROGRAMMING; ROBOTICS; ROBOTS;

EVOLUTIONARY ALGORITHMS;

EID: 77951164994     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIRA.2009.5423163     Document Type: Conference Paper

References (25)

1. S.D. Bungay, R.A. Poirier, and R.J. Charron, "Optimization of transition state structures using genetic algorithms", Journal of Mathematical Chemistry, 2004. 28(4): p. 389-401.
2. M. M. H. Ellabaan, Y. S. Ong, "Valley-Adaptive Clearing Scheme for Multimodal Optimization Evolutionary Search", The International Conference on Intelligent Systems Design and Applications, ISDA09, 30th Nov - 2nd Dec. Pisa, Italy
3. L. Lucchese and S.K. Mitra. Using saddle points for subpixel feature detection in camera calibration targets. In Proceedings of the 2002, Asia Pacific Conference on Circuits and Systems, volume 2, pages 191-195, 2002.
4. C. Sminchisescu, B. Triggs, Building roadmaps of minima and transitions in visual models, International Journal of Computer Vision 61 (1), pp. 81-101, 2005.
5. K. K. Lim, Y. S. Ong, M. H. Lim, X. Chen and A. Agarwal, 'Hybrid Ant Colony Algorithm for Path Planning in Sparse Graphs', Soft Computing Journal, pp. 981-994, 2007
6. M. Lassonde, "Approximation, optimization and mathematical economics" Springer, 2001.
7. G. M. Keserü, I. Kolossváry "Molecular mechanics and conformational analysis in drug design ", Oxford; Malden, Mass.: Blackwell Science, 1999.
8. D.S. Jones, B.D. Sleeman, "Differential Equations and Mathematical Biology" Chapman & Hall/CRC; 2003.
9. Y. S. Ong, P.B. Nair and A.J. Keane, "Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling", American Institute of Aeronautics and Astronautics Journal, 2003, Vol.41, No.4, pp. 687-696.
10. Y. S. Ong, P. B. Nair and K. Y. Lum, "Max-Min Surrogate-Assisted Evolutionary Algorithm for Robust Design", IEEE Transactions on Evolutionary Computation, Vol.10, No.4, pp. 392-404, August 2006.
11. F. Neri, J. Toivanen, G. L. Cascella and Y. S. Ong, "An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Special Issue on Computational Intelligence Approaches in Computational Biology and Bioinformatics, 2007, Vol. 4, No. 2, pp. 264-278.
12. J. Tang, M. H. Lim and Y. S. Ong, "Diversity-Adaptive Parallel Memetic Algorithm for Solving Large Scale Combinatorial Optimization Problems", Soft Computing Journal, 2007, Vol.11, No.9, pp. 873-888.
13. Q. C. Nguyen, Y. S. Ong, H. Soh and Jer-Lai Kuo, "Multiscale Approach to Explore the Potential Energy Surface of Water Clusters (H2O)8 n<=8", Journal of Phys. Chem. A, Vol.112, No.28, pp. 6257 - 6261, 2008.
14. Z. Z. Zhou, Y. S. Ong, M. H. Lim and B. S. Lee, "Memetic Algorithm using Multi-Surrogates for Computationally Expensive Optimization Problems", Soft Computing Journal, Vol.11, No.10, pp. 957- 971, August 2007.
15. R. Judson, Genetic algorithms and their use in chemistry, Reviews in Computational Chemistry 10 (1997) 1-73. (Pubitemid 127472528)
16. D. Lim, Y. S. Ong, Y. Jin, B. Sendhoff and B. S. Lee, "Efficient Hierarchical Parallel Genetic Algorithms Using Grid Computing", Future Generation Computer Systems: The International Journal of Grid Computing: Theory, Methods and Applications, 2007, Vol.23 , No.4 , pp. 658-670.
17. S. Trygubenko and D. Wales, "A Doubly Nudged Elastic Band Method for Finding Transition States". Chem. Phy., 2004. 120(5): p. 2082-2094.
18. J.M.d. Campo, and A.M. Koster, "A hierarchical transition state search algorithm", Chem. Phy., 2008. 129: p. 024107-24112
19. REDDY, C.K. and H.-D. CHIANG, "A Stability Boundary Based Method for Finding Saddle Points on Potential Energy Surfaces". JOURNAL OF COMPUTATIONAL BIOLOGY, 2006. 13: p. 745-766.
20. G. Henkelman and H. Jonsson, "A dimer method for finding saddle points on high dimensional potential surfaces using only first derivatives". Chem. Phy., 1999. 15(111): p. 7010-7022.
21. R.A. Olsen, "Comparison of methods for finding saddle points without knowledge of the final states". Chem. Phy., 2004. 121(20): p. 9776-9792.
22. P. Chaudhury, and S.P. Bhattacharyya, "A simulated annealing based technique for locating first-order saddle points on multidimensional surface and constructing reaction paths: several model studies". Theo. Chem., 1998. 429: p. 175-186.
23. P. Chaudhury, S.P. Bhattacharyya, and W. Quapp, "A genetic algorithm based technique for locating first-order saddle point using only a gradient dominated recipe". Chemical Physics 2000. 253: p. 295-303.
24. J. Branke, "Evolutionary Optimization in Dynamic Environments". 2002: Kluwer Academic Publishers.
25. H. Soh, Y. S. Ong, Q. C. Nguyen, Q. H. Nguyen, M. S. Habibullah, T. Hung and J.-L. Kuo, "Discovering Unique, Low-Energy Pure Water Isomers: Memetic Exploration, Optimization and Landscape Analysis", IEEE Transactions on Evolutionary Computation, Accepted August 2009.