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Searching the landscape of flux vacua with genetic algorithms
Journal of High Energy Physics, 2019 In this paper, we employ genetic algorithms to explore the landscape of type IIB flux vacua. We show that genetic algorithms can efficiently scan the landscape for viable solutions satisfying various criteria. More specifically, we consider a symmetric T
Alex Cole, Andreas Schachner, Gary Shiu
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Genetic algorithms applied to the scheduling of the hubble space telescope [PDF]
, 1989 Jeffrey L. Sponsler
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Optimal Design of a Cam Mechanism with Translating Flat-Face Follower using Genetic Algorithm [PDF]
Tribology in Industry, 2013 The optimum design of a cam mechanism is a time consuming task, due to the numerous alternatives considerations. In the present work, the problem of design parameters optimization of a cam mechanism with translating flat - face follower is investigated ...
I. Tsiafis +3 more
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A Genetic Algorithm Tool (splicer) for Complex Scheduling Problems and the Space Station Freedom Resupply Problem [PDF]
, 1993 The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights ...
Valenzuela-Rendon, Manuel, Wang, Lui
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The Evolution of Genetic Algorithms: Towards Massive Parallelism [PDF]
, 1993 Shumeet Baluja
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Genetic and evolutionary algorithms come of age [PDF]
, 1994 David E. Goldberg
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Reduced representation model of protein structure prediction: Statistical potential and genetic algorithms [PDF]
, 1993 Shaojian Sun
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Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest.
Bayer, Steven E., Wang, Lui
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On the Application of Genetic Algorithms to Differential Equations [PDF]
Genetic algorithms can be used in order to solve optimization problems. Such a technique may be used in order to solve differential equations.differential equations; genetic algorithms;
Mateescu, George Daniel
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The genetic algorithm in science
Pesticide Science, 1995 AbstractAlgorithms developed for use in the study of artificial intelligence also show promise in such quite different fields as the physical and life sciences. These methods may have advantages in speed, scope, or both, over more conventional scientific methods, and expand the range of algorithmic techniques open to the scientist. The mechanism of one
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