Open Access
Issue
MATEC Web Conf.
Volume 246, 2018
2018 International Symposium on Water System Operations (ISWSO 2018)
Article Number 01003
Number of page(s) 6
Section Main Session: Water System Operations
DOI https://doi.org/10.1051/matecconf/201824601003
Published online 07 December 2018
  1. C.A.C. Coello, Theoretical and numerical constrainthandling techniques used with evolutionary algorithms: a survey of the state of the art, Comput. Methods Appl. Mech. Eng. 191(2002)1245-1287. [CrossRef] [Google Scholar]
  2. D.E. Goldberg Genetic. Algorithms in search optimization and machine learning Boston: Addison-Wesley Longman Publishing Co. 1989 [Google Scholar]
  3. Deb K, Agrawal RB. Simulated binary crossover for continuous search space. Complex Systems, 1995, 9(6): 115-148. [Google Scholar]
  4. M. Takahashi, H. Kita. A Crossover Operator Using Independent Component Analysis for Real-Coded Genetic Algorithm, in Proceedings of the 2001 Congress on Evolutionary Computation, (2001) 643-649 [CrossRef] [Google Scholar]
  5. Holland J. Adaptation in natural and artificial systems. The University of Michigan Press, 1975, Ann Arbour. [Google Scholar]
  6. H.R. Howson, N.G.F. Sancho, A two-stage algorithm for sequential decisions problems. INFOR II 2 (1973)163-176. [Google Scholar]
  7. H.R. Howson, N.G.F. Sancho, A new algorithm for the solution of multi-state dynamic programming problems, Math.Programm. 8(1975)104-116. [CrossRef] [Google Scholar]
  8. J.H. Holland, Adaptation in Nature and Artificial Systems, University of Michigan Press, Ann Arbor, 1975. [Google Scholar]
  9. J. Nelder, R. Mead, A simplex method for function minimization. Computer Journal, (1965)308-313. [CrossRef] [Google Scholar]
  10. K.V. Price, R.M. Storn, Differential evolution - a simple evolution strategy for fast optimization. Dr. Dobb’s Journal, 22(1997)18-24. [Google Scholar]
  11. K.V. Price, R.M. Storn, J.A. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, Springer-Verlag, New York, 2005. [Google Scholar]
  12. Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, New York, 1996. [CrossRef] [Google Scholar]
  13. Ono I, Kita H, Kobayashi S. A robust real-coded genetic algorithm using unimodal normal distribution crossover augmented by uniform crossover: effects of self-adaptation of crossover probabilities. Proceedings of the Genetic and Evolutionary Computation Conference. San Mateo: Morgan Kaufmann Publishers, 1999, 496~503. [Google Scholar]
  14. Price K, Strom R, Lampinen J. Differential evolution: a practical approach to global optimization [M]. Springer Science & Business Media, 2006. [Google Scholar]
  15. Shu-Kai S. Fan, Yun-Chia Liang, Erwie Zahara, A genetic algorithm and a particle swarm optimizer hybridized with Nelder–Mead simplex search. Computer and Industrial Engineering. 50(2006)401-425. [CrossRef] [Google Scholar]
  16. S. Simonovic, The implicit stochastic model for reservoir yield optimization, Water Resour Res., 23(1987)2159-2165. [CrossRef] [Google Scholar]
  17. Storn R, Price K. Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces [J]. Journal of global optimization, 1997, 11(4): 341-359. [CrossRef] [MathSciNet] [Google Scholar]
  18. Takahashi M, Kita H. A crossover operator using independent component analysis for real-coded genetic algorithm. Proceedings of the 2001 Congress on Evolutionary Computation, 2001, pp. 643-649. [CrossRef] [Google Scholar]
  19. Thangavelu S, Velayutham C S. An investigation on mixing heterogeneous differential evolution variants in a distributed framework [M]. Inderscience Publishers, 2015. [Google Scholar]
  20. Tsutsui S, Yamamura M, Higuchi T. Multi-parent recombination with simplex crossover in real coded genetic algorithms. Proceedings of the Genetic and Evolutionary Computation Conference. San Mateo: Morgan Kaufmann Publishers, 1999. 657~664. [Google Scholar]
  21. Wen X, Xia Q, Zhao Y. An effective genetic algorithm for circularity error unified evaluation [J]. International Journal of Machine Tools & Manufacture, 2006, 46(14):1770-1777. [CrossRef] [Google Scholar]
  22. W. Splendy, G.R. Hext, F.R. Himsworth Sequential application of simplex design in optimization and evolutionary design. Technometrics (1962) 441-461. [Google Scholar]
  23. X. Liu, S. Guo, P. Liu, L. Chen, X. Li, Deriving optimal refill rules for multi-purpose reservoir operation, Water Resour Manage 25 (2011)431-448. [CrossRef] [Google Scholar]
  24. Yan X, Liu H, Zhu Z, et al. Hybrid genetic algorithm for engineering design problems [J]. Cluster Computing, 2016, 13(9):1-13. [Google Scholar]
  25. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, New York, 1996. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.