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ORCIDMemetic Computing, Volume 1
Volume 1, Number 1, March 2009
- Meng-Hiot Lim, Steven M. Gustafson, Natalio Krasnogor
, Yew-Soon Ong:
Editorial to the first issue. 1-2 - Xin Yu, Ke Tang, Tianshi Chen, Xin Yao:
Empirical analysis of evolutionary algorithms with immigrants schemes for dynamic optimization. 3-24 - Gregory Z. Gutin, Daniel Karapetyan:
A selection of useful theoretical tools for the design and analysis of optimization heuristics. 25-34 - Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Research topics in discrete estimation of distribution algorithms based on factorizations. 35-54 - Jaume Bacardit, Edmund K. Burke, Natalio Krasnogor:
Improving the scalability of rule-based evolutionary learning. 55-67 - S. M. Kamrul Hasan, Ruhul A. Sarker, Daryl Essam, David Cornforth:
Memetic algorithms for solving job-shop scheduling problems. 69-83
Volume 1, Number 2, June 2009
- Ryan J. Meuth, Meng-Hiot Lim, Yew-Soon Ong, Donald C. Wunsch:
A proposition on memes and meta-memes in computing for higher-order learning. 85-100 - Thomas Fischer, Kerstin Bauer, Peter Merz:
Solving the routing and wavelength assignment problem with a multilevel distributed memetic algorithm. 101-123 - James M. Whitacre, Ruhul A. Sarker, Q. Tuan Pham:
Making and breaking power laws in evolutionary algorithm population dynamics. 125-137 - Claus de Castro Aranha, Hitoshi Iba:
The Memetic Tree-based Genetic Algorithm and its application to Portfolio Optimization. 139-151 - Ferrante Neri, Ville Tirronen:
Scale factor local search in differential evolution. 153-171
Volume 1, Number 3, November 2009
- Meng-Hiot Lim, Steven M. Gustafson, Natalio Krasnogor, Yew-Soon Ong:
Editorial. 173-174 - Minh Nghia Le, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff:
Lamarckian memetic algorithms: local optimum and connectivity structure analysis. 175-190 - Chuan-Kang Ting, Cheng-Feng Ko, Chih-Hui Huang:
Selecting survivors in genetic algorithm using tabu search strategies. 191-203 - Mohamed Bahy Bader-El-Den, Riccardo Poli, Shaheen Fatima:
Evolving timetabling heuristics using a grammar-based genetic programming hyper-heuristic framework. 205-219 - Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe:
Tuning membership functions of kernel fuzzy classifiers by maximizing margins. 221-228 - Heikki Ilmari Martikka, Ilkka Pöllänen:
Multi-objective optimization by technical laws and heuristics. 229-238
Volume 1, Number 4, December 2009
- Shaoning Pang, Tao Ban:
Guest editorial: Thematic issue on 'Adaptive Soft Computing Techniques and Applications'. 239-240 - Petr Kadlec, Bogdan Gabrys:
Architecture for development of adaptive on-line prediction models. 241-269 - Koichiro Yamauchi:
Optimal incremental learning under covariate shift. 271-279 - Malay Bhattacharyya, Sanghamitra Bandyopadhyay:
Solving maximum fuzzy clique problem with neural networks and its applications. 281-290 - Stephan Kirstein, Alexander Denecke, Stephan Hasler, Heiko Wersing, Horst-Michael Gross, Edgar Körner:
A vision architecture for unconstrained and incremental learning of multiple categories. 291-304 - Pitoyo Hartono, Sachiko Kakita:
Fast reinforcement learning for simple physical robots. 305-313
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