Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Spin-flip symmetry and synchronization
Evolutionary Computation
The Effect of Spin-Flip Symmetry on the Performance of the Simple GA
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
An Analysis Of The Role Of Offspring Population Size In EAs
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
From Twomax To The Ising Model: Easy And Hard Symmetrical Problems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Symmetry in the representation of an optimization problem
Symmetry in the representation of an optimization problem
On the Choice of the Offspring Population Size in Evolutionary Algorithms
Evolutionary Computation
Hierarchical BOA solves ising spin glasses and MAXSAT
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
The analysis of a recombinative hill-climber on H-IFF
IEEE Transactions on Evolutionary Computation
Computational complexity and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Theoretical analysis of diversity mechanisms for global exploration
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Ignoble Trails - Where Crossover Is Provably Harmful
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Crossover Can Be Constructive When Computing Unique Input Output Sequences
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Single- and multi-objective evolutionary algorithms for graph bisectioning
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Computational complexity and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Analysis of diversity-preserving mechanisms for global exploration*
Evolutionary Computation
Computational complexity and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
How crossover helps in pseudo-boolean optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An analysis on recombination in multi-objective evolutionary optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Running time analysis of Ant Colony Optimization for shortest path problems
Journal of Discrete Algorithms
Crossover speeds up building-block assembly
Proceedings of the 14th annual conference on Genetic and evolutionary computation
An analysis on recombination in multi-objective evolutionary optimization
Artificial Intelligence
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The investigation of genetic and evolutionary algorithms on Ising model problems gives much insight into how these algorithms work as adaptation schemes. The one-dimensional Ising model with periodic boundary conditions has been considered as a typical example with a clear building block structure suited well for two-point crossover. It has been claimed that GAs based on recombination and appropriate diversity-preserving methods by far outperform EAs based on mutation only. Here, a rigorous analysis of the expected optimization time proves that mutation-based EAs are surprisingly effective. The (1 +λ) EA with an appropriate λ-value is almost as efficient as typical GAs. Moreover, it is proved that specialized GAs do even better and this holds for two-point crossover as well as for one-point crossover.