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Hybridize, Hybridize And Hybridize Again  (Make Corrections)  
Hugues Bersini



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Abstract: These last years two global optimizations methods hybridizing Evolutionary Algorithms (EA, but mainly GA) with hill-climbing methods have been investigated. The first one involves two interwoven levels of optimization: Evolution (EA) and Individual Learning (hill-climbing), which cooperate in the global optimization process. The second one consists of modifying EA by the introduction of new genetic operators or by the alteration of traditional ones in such a way that these new operators reflect ... (Update)

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BibTeX entry:   (Update)

@misc{ bersini-hybridize,
  author = "Hugues Bersini",
  title = "Hybridize, Hybridize And Hybridize Again",
  url = "citeseer.ist.psu.edu/361820.html" }
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548   Genetic Algorithms + Data Structures = Evolution Programs (context) - Michalewicz - 1992
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246   Genetic algorithms in search, optimization, and machine lear.. - Goldberg - 1989
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16   Managing Genetic Search in Job Shop Scheduling (context) - Uckun, Bagchi et al. - 1993
15   The immune recruitment mechanism: A selective evolutionary s.. (context) - Bersini, Varela - 1991  DBLP
15   A genetic algorithm for parallel simulated annealing (context) - Mahfoud, Goldberg - 1992
14   An Analysis of Selection Procedures with Particular Attentio.. (context) - Maza, Tidor - 1993  ACM   DBLP
14   A Hybrid Genetic Algorithm for Task Allocation in Multicoput.. (context) - Mansour, Fox - 1991
11   A Hybrid Search for Genetic Algorithms: Combining Genetic Al.. (context) - Kido, Kitano - 1993
3   In Search of A Good Evolution-Optimization Crossover (context) - Bersini, Seront - 1992  DBLP
2   Optimizing with the Immune Recruitment Mechanism (context) - Bersini, Seront - 1993
1   STEP: The Easiest Way to Optimize a Function (context) - Langerman, Seront - 1994

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