Proceedings ArticleDOI
On genetic algorithms
Eric B. Baum,Dan Boneh,Charles Garrett +2 more
- pp 230-239
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C Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach in some regimes, and some new large deviation bounds on this submartingale enable us to determine the running time of the algorithm.Abstract:
We analyze the performance of a Genetic Type Algorithm we call Culling and a variety of other algorithms on a problem we refer to as ASP. Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach . . in some regimes. We show that the problem of learning the Ising perception is reducible to noisy ASP. These results provide an example of a rigorous analysis of GA’s and give insight into when and how C,A’s can beat competing methods. To analyze the genetic algorithm, we view it as a special type of submartingale. We prove some new large deviation bounds on this submartingale w~ich enable us to determine the running time of the algorithm.read more
Citations
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Journal ArticleDOI
Performance analysis of evolution strategies with multi-recombination in high-dimensional R N -search spaces disturbed by noise
Dirk V. Arnold,Hans-Georg Beyer +1 more
TL;DR: It is shown that, in contrast to results obtained in the limit of infinite search space dimensionality, there is a finite optimal population size above which the efficiency of the strategy declines, and that therefore it is not possible to attain the efficiency that can be achieved in the absence of noise by increasing the population size.
Journal ArticleDOI
The Use of Genetic Algorithms in Response Surface Methodology
TL;DR: This paper shows how Genetic Algorithms can be used when RSM is applied and an optimisation process is required.
Proceedings ArticleDOI
Evolutionary Ensemble Creation and Thinning
Jared Sylvester,Nitesh V. Chawla +1 more
TL;DR: The approach provides a general-purpose framework for evolutionary ensembles, allowing them to build on top of any collection of classifiers, whether they be heterogeneous or homogeneous.
Journal ArticleDOI
Genetic neuro-scheduler: A new approach for job shop scheduling
TL;DR: A hybrid approach between two new techniques, genetic algorithms and artificial neural network is described for generating job shop schedules in a discrete manufacturing environment based on nonlinear multiobjective function and results indicate that the proposed approach is consistently better than those of heuristic algorithms used extensively in industry.
Journal ArticleDOI
A new "doctor and patient" optimization algorithm: An application to energy commitment problem
Mohammad Javad Dehghani,Mohammad Mardaneh,Josep M. Guerrero,Om P. Malik,Ricardo A. Ramirez-Mendoza,Jose Matas,Juan C. Vasquez,Lizeth Parra-Arroyo +7 more
TL;DR: The authors present a new optimization algorithm named doctor and patient optimization (DPO), designed by simulating the process of treating patients by a physician, which is successfully applied to solve the energy commitment problem for a power system supplied by a multiple energy carriers system.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book ChapterDOI
Probability Inequalities for sums of Bounded Random Variables
TL;DR: In this article, upper bounds for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt are derived for certain sums of dependent random variables such as U statistics.
Book
The Probabilistic Method
TL;DR: A particular set of problems - all dealing with “good” colorings of an underlying set of points relative to a given family of sets - is explored.