Black box search: framework and methods
Black box search: framework and methods
Proceedings of the 9th annual conference on Genetic and evolutionary computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Remarks on a recent paper on the "no free lunch" theorems
IEEE Transactions on Evolutionary Computation
Free lunches on the discrete Lipschitz class
Theoretical Computer Science
Unbiased black box search algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A measure-theoretic analysis of stochastic optimization
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Evolutionary Computation
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
A study of search algorithms' optimization speed
Journal of Combinatorial Optimization
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Since its inception, the “No Free Lunch” theorem (NFL) has concerned the application of symmetry results rather than the symmetries themselves. In our view, the conflation of result and application obscures the simplicity, generality, and power of the symmetries involved. This paper separates result from application, focusing on and clarifying the nature of underlying symmetries. The result is a general set-theoretic version of NFL which speaks to symmetries when arbitrary domains and co-domains are involved. Although our framework is deterministic, we note situations where our deterministic set-theoretic results speak nevertheless to stochastic algorithms.