Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity-Reference-Cited by-同舟云学术

Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity

Published:2016 Issue: Volume: Page:235-250
ISSN:0302-9743
Container-title:Evolutionary Computation in Combinatorial Optimization
language:
Short-container-title:

Author:

Michalak Krzysztof

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-30698-8_16

Reference31 articles.

1. Baluja, S.: Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning. Technical report, Pittsburgh (1994)

2. LNCS;M Bessaou,2000

3. Brest, J., et al.: Dynamic optimization using self-adaptive differential evolution. In: IEEE Congress on Evolutionary Computation, pp. 415–422. IEEE (2009)

4. Chen, J., Wineberg, M.: Enhancement of the shifting balance genetic algorithm for highly multimodal problems. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation, pp. 744–751. IEEE Press, Portland (2004)

5. Lecture Notes in Computer Science;L delaOssa,2004

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Comparative Study of Heuristics and Meta-heuristic Algorithms with Issues in WSN;Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications;2020-10-18

2. Multi-population techniques in nature inspired optimization algorithms: A comprehensive survey;Swarm and Evolutionary Computation;2019-02

3. Estimation of Distribution Algorithms for the Firefighter Problem;Evolutionary Computation in Combinatorial Optimization;2017