A survey of optimization by building and using probabilistic models
作者： M. Pelikan , D.E. Goldberg , F. Lobo
关键词:
摘要: This paper summarizes the research on population-based probabilistic search algorithms based on modeling promising solutions by estimating their probability distribution and using …
springer.com
fernandolobo.info 参考文章(38)
Thilo Mahnig, Heinz Muhlenbein, Convergence Theory and Applications of the Factorized Distribution Algorithm computer and information technology. ,vol. 7, pp. 19- 32 ,(2015)
Shigenobu Kobayashi, Isao Ono, A Real Coded Genetic Algorithm for Function Optimization Using Unimodal Normal Distributed Crossover. Proc. 7th ICGA, 1997. pp. 246- 253 ,(1997)
David E. Goldberg, Dimitri Knjazew, OMEGA - ordering messy GA: solving permutation problems with the fast messy genetic algorithm and random keys genetic and evolutionary computation conference. pp. 181- 188 ,(2000)
Marcus Frean, Tom Downs, Marcus Gallagher, Real-valued evolutionary optimization using a flexible probability density estimator genetic and evolutionary computation conference. ,vol. 1, pp. 840- 846 ,(1999)
Armin Heinzl, David E. Goldberg, Franz Rothlauf, Bad codings and the utility of well-designed genetic algorithms genetic and evolutionary computation conference. pp. 355- 362 ,(2000)
Kalyanmoy Deb, Ram Bhushan Agrawal, Simulated Binary Crossover for Continuous Search Space. Complex Systems. ,vol. 9, ,(1995)
R. Roy, 武 古橋, P. Chawdhry, Advances in Soft Computing: Engineering Design and Manufacturing ,(1998)
Shummet Baluja, Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning Carnegie Mellon University. ,(1994)
John H. Holland, Adaptation in natural and artificial systems ,(1992)
Rafał Sałustowicz, Jürgen Schmidhuber, Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space european conference on machine learning. ,vol. 1224, pp. 213- 220 ,(1997) , 10.1007/3-540-62858-4_86