(Enter summary)
Abstract: This paper theoretically compares the performance
of simulated annealing and evolutionary algorithms.
Our main result is that under mild conditions
a wide variety of evolutionary algorithms
can be shown to have greater probability of success
than simulated annealing after a sufficiently
large number of function evaluations. This class
of EAs includes variants of evolution strategies
and evolutionary programming, genetic programming,
the canonical genetic algorithm, as well as
a variety of... (Update)
Context of citations to this paper: More
...slow cooling schedule in order to converge to an optimal solution with high probabilities. Genetic algorithm (GA) [112, 108, 77, 62, 109, 136, 118, 123, 86, 58, 35] is a stochastic global optimization algorithm . It maintains a population of candidate points in each generation....
...moves, it is generally not as e#cient as local search methods that only accept down hill moves. Genetic algorithm (GA) [80, 59, 133, 161, 142, 146, 93], a typical global optimization algorithm with reachability, roots itself in nature s rule of fitness to survive. As...
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BibTeX entry: (Update)
William E. Hart. A theoretical comparison of evolutionary algorithms and simulated annealing. In Evolutionary Programming V, pages 147--154, Cambridge, MA, 1996. MIT Press. http://citeseer.ist.psu.edu/hart96theoretical.html More
@inproceedings{ hart96theoretical,
author = "William E. Hart",
title = "A Theoretical Comparison of Evolutionary Algorithms and Simulated Annealing",
booktitle = "Evolutionary {P}rogramming {V}: {P}roc.~of the {F}ifth {A}nnual {C}onf.~on {E}volutionary {P}rogramming",
publisher = "MIT Press",
address = "Cambridge, MA",
editor = "Lawrence J. Fogel and Peter J. Angeline and Thomas B{\"a}ck",
pages = "147--154",
year = "1996",
url = "citeseer.ist.psu.edu/hart96theoretical.html" }
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1527
Optimization by simulated annealing
- Kirkpatrick, Gelatt et al. - 1983
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Genetic programming: On Programming Computers by Means of Na.. (context) - Koza - 1992
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An Analysis of the Behavior of a Class of Genetic Adaptive S.. (context) - De Jong - 1975
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Simulated Annealing: Theory and Applications (context) - van Laarhoven, Aarts - 1987
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Evolutionary Computation (context) - Fogel - 1995
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Finite Markov chain analysis of genetic algorithms (context) - Goldberg, Segrest - 1987
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An overview of evolutionary algorithms for parameter optimiz.. (context) - ack, Schwefel - 1993
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A simulated annealing like convergence theory for the simple.. (context) - Davis, Principe - 1991
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Genetic local search algorithms for the traveling salesman p.. (context) - Ulder, Aarts et al. - 1990
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Solving partitioning problems with genetic algorithms (context) - Jones, Beltramo - 1991
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Modelling genetic algorithms with Markov chains (context) - Nix, Vose - 1992
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The application of genetic algorithms to resource scheduling (context) - Syswerda, Palmucci - 1991
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A Markov chain analysis on a genetic algorithm (context) - Suzuki - 1993
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Convergence and finite-time behavior of simulated annealing (context) - Mitra, Romeo et al. - 1986
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Bounding the probability of success of stochastic methods fo.. (context) - Ferreira, Zerovnik - 1993
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AddisonWesley Publishing Co (context) - Goldberg, in et al. - 1989
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Genetic algorithm for clustering with an ordered representat.. (context) - Bhuyan, Raghavan et al. - 1991
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Massively parallel simulated annealing and its relation to e..
- Rudolph - 1993
9
the convergence rate of annealing processes (context) - Chaing, Chow - 1988
6
Evolving aesthetic sorting networks using developmental gram.. (context) - Belew, Kammeyer - 1993
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Modeling simple genetic algorithms for permutation problems
- Whitley, Yoo - 1995
2
A comparison of genetic sequence operators (context) - Starkweather, McDaniel et al. - 1991
1
IEEE Transactions on Neural Networks (context) - of, algorithms - 1994
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