Download e-book for kindle: Advances in Computation and Intelligence: Second by Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, Changhe

By Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, Changhe Li, Ming Yang, Yan Li (auth.), Lishan Kang, Yong Liu, Sanyou Zeng (eds.)

ISBN-10: 3540745807

ISBN-13: 9783540745808

This publication constitutes the refereed court cases of the second one overseas Symposium on Intelligence Computation and functions, ISICA 2007, held in Wuhan, China, in September 2007. The seventy one revised complete papers have been conscientiously reviewed and chosen from approximately 1000 submissions. the subjects contain evolutionary computation, evolutionary studying, neural networks, swarms, trend popularity, info mining and others.

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Extra info for Advances in Computation and Intelligence: Second International Symposium, ISICA 2007 Wuhan, China, September 21-23, 2007 Proceedings

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Keywords: Reference point based NSGA-II, EMO, Constrained optimization, SBX, SQP, hybrid procedure, multi-objective optimization. 1 Introduction In practice, optimization problems always have some constraints involving physical, geometric or other limitations restricting the search. To handle such constraints, various methodologies are used. Of these, the penalty parameter based approaches are commonly used. One difficulty in these methods is to set an appropriate value of the penalty parameters.

2 Earth-Mars-Venus-Mercury Mission Next, we apply GOSpel and Table 2. Earth-Mars-Venus-Mercury trajectories. Dates compare its results with another are in mm/dd/yy. 9465 Mars and Venus. 9958 2005 for a year. 326 minimum time of flight. 145 of arrival at Mars and Venus and the corresponding arrival and departure velocities are also shown in the table. The GOSpel solutions are shown in Figure 2 for both objectives. In this case, we allow only two-planet swing-by trajectories to be considered. Thus, direct or one-planet swing-by option is not considered.

This proved that the density is really important, and could achieve more distribution solutions. Acknowledgments. Authors acknowledge the supports from the Natural Science Foundation of Hunan Province (05JJ30125), and the Keystone Science Research Project of the Education Office of Hunan Province (06A074). References 1. : The Pareto envelope based selection algorithm for multi-objective optimization. In: Proceedings of the Parallel Problem Solving from Nature VI Conference, pp. 839–848 (2000) 2.

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Advances in Computation and Intelligence: Second International Symposium, ISICA 2007 Wuhan, China, September 21-23, 2007 Proceedings by Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, Changhe Li, Ming Yang, Yan Li (auth.), Lishan Kang, Yong Liu, Sanyou Zeng (eds.)


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