Evolutionary Computation in Dynamic and Uncertain Environments 2007
Shengxiang Yang, Yew-Soon Ong, Yaochu Jin (Eds.):
Evolutionary Computation in Dynamic and Uncertain Environments.
Studies in Computational Intelligence Vol. 51 Springer 2007, ISBN 978-3-540-49772-1 BibTeX
- Shengxiang Yang:
Explicit Memory Schemes for Evolutionary Algorithms in Dynamic Environments.
3-28
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- Tim Blackwell:
Particle Swarm Optimization in Dynamic Environments.
29-49
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- Lutz Schönemann:
Evolution Strategies in Dynamic Environments.
51-77
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- Sanyou Y. Zeng, Hui Shi, Lishan Kang, Lixin Ding:
Orthogonal Dynamic Hill Climbing Algorithm: ODHC.
79-104
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- Renato Tinós, Shengxiang Yang:
Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments.
105-127
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- Peter A. N. Bosman:
Learning and Anticipation in Online Dynamic Optimization.
129-152
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- Hai Huong Dam, Chris Lokan, Hussein A. Abbass:
Evolutionary Online Data Mining: An Investigation in a Dynamic Environment.
153-178
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- Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac:
Adaptive Business Intelligence: Three Case Studies.
179-196
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- Frederico Paiva Quintão, Fabíola Guerra Nakamura, Geraldo Robson Mateus:
Evolutionary Algorithms for Combinatorial Problems in the Uncertain Environment of the Wireless Sensor Networks.
197-222
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- Lars Gräning, Yaochu Jin, Bernhard Sendhoff:
Individual-based Management of Meta-models for Evolutionary Optimization with Application to Three-Dimensional Blade Optimization.
225-250
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- Wenbin Song:
Evolutionary Shape Optimization Using Gaussian Processes.
251-267
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- Margarita Reyes Sierra, Carlos A. Coello Coello:
A Study of Techniques to Improve the Efficiency of a Multi-Objective Particle Swarm Optimizer.
269-296
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- Kalyanmoy Deb, Pawan K. S. Nain:
An Evolutionary Multi-objective Adaptive Meta-modeling Procedure Using Artificial Neural Networks.
297-322
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- Yolanda Mack, Tushar Goel, Wei Shyy, Raphael T. Haftka:
Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design.
323-342
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- Ferrante Neri, Raino A. E. Mäkinen:
Hierarchical Evolutionary Algorithms and Noise Compensation via Adaptation.
345-369
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- Kagan Tumer, Adrian K. Agogino:
Evolving Multi Rover Systems in Dynamic and Noisy Environments.
371-387
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- Yoel Tenne, Steven William Armfield:
A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions.
389-415
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- Masaru Tezuka, Masaharu Munetomo, Kiyoshi Akama:
Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem.
417-434
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- Dudy Lim, Yew-Soon Ong, Meng-Hiot Lim, Yaochu Jin:
Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty.
437-456
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- Chi Keong Goh, Kay Chen Tan:
Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms.
457-478
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- Jianjun Hu, Shaobo Li, Erik D. Goodman:
Evolutionary Robust Design of Analog Filters Using Genetic Programming.
479-496
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- Hisashi Handa, Lee Chapman, Xin Yao:
Robust Salting Route Optimization Using Evolutionary Algorithms.
497-517
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- Zhun Fan, Jiachuan Wang, Min Wen, Erik D. Goodman, Ronald C. Rosenberg:
An Evolutionary Approach For Robust Layout Synthesis of MEMS.
519-542
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- Claudio M. Rocco Sanseverino, Daniel E. Salazar Aponte:
A Hybrid Approach Based on Evolutionary Strategies and Interval Arithmetic to Perform Robust Designs.
543-564
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- Carlos Barrico, Carlos Henggeler Antunes:
An Evolutionary Approach for Assessing the Degree of Robustness of Solutions to Multi-Objective Models.
565-582
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- Qing Ling, Gang Wu, Qiuping Wang:
Deterministic Robust Optimal Design Based on Standard Crowding Genetic Algorithm.
583-598
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Copyright © Sat May 16 22:55:05 2009
by Michael Ley (ley@uni-trier.de)