Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Recent progress in unconstrained nonlinear optimization without derivatives
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
Communications of the ACM
Dynamic Programming and Optimal Control, Two Volume Set
Dynamic Programming and Optimal Control, Two Volume Set
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Programming
The Journal of Machine Learning Research
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Not all linear functions are equally difficult for the compact genetic algorithm
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Convergence results for the (1, λ)-SA-ES using the theory of ϕ-irreducible Markov chains
Theoretical Computer Science
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
On the benefits of inoculation, an example in train scheduling
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An informational approach to the global optimization of expensive-to-evaluate functions
Journal of Global Optimization
General lower bounds for evolutionary algorithms
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Algorithms (x, sigma, eta): quasi-random mutations for evolution strategies
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Lower Bounds for Evolution Strategies Using VC-Dimension
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Extreme Value Based Adaptive Operator Selection
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Toward comparison-based adaptive operator selection
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Comparison-based optimizers need comparison-based surrogates
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Bandit-based estimation of distribution algorithms for noisy optimization: rigorous runtime analysis
LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
Comparison-based complexity of multiobjective optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good performance. The theoretical analysis of these algorithms usually focuses on convergence rates. This paper presents a mathematical study of randomized search heuristics which use comparison based selection mechanism. The two main results are that comparison-based algorithms are the best algorithms for some robustness criteria and that introducing randomness in the choice of offspring improves the anytime behavior of the algorithm. An original Estimation of Distribution Algorithm combining both results is proposed and successfully experimented.