Cooling schedules for optimal annealing
Mathematics of Operations Research
An introduction to genetic algorithms
An introduction to genetic algorithms
Finite Markov chain results in evolutionary computation: a tour d'horizon
Fundamenta Informaticae
The theory of evolution strategies
The theory of evolution strategies
Theoretical Computer Science
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
How to analyse evolutionary algorithms
Theoretical Computer Science - Natural computing
Theoretical Computer Science
On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics
Combinatorics, Probability and Computing
Convergence results for the (1, λ)-SA-ES using the theory of ϕ-irreducible Markov chains
Theoretical Computer Science
Runtime Analysis of the (μ+1) EA on Simple Pseudo-Boolean Functions
Evolutionary Computation
Experimental Research in Evolutionary Computation: The New Experimentalism (Natural Computing Series)
Algorithmic analysis of a basic evolutionary algorithm for continuous optimization
Theoretical Computer Science
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Hitting times of the global optimum for evolutionary algorithms are usually available for simple unimodal problems or for simplified algorithms. In discrete problems, the number of results that relate the convergence rate of evolution strategies to the geometry of the optimisation landscape is restricted to a few theoretical studies. This article introduces a variant of the canonical (μ+ 茂戮驴)-ES, called the Poisson-ES, for which the number of offspring is not deterministic, but is instead sampled from a Poisson distribution with mean 茂戮驴. After a slight change on the rank-based selection for the μparents, and assuming that the number of offspring is small, we show that the convergence rate of the new algorithm is dependent on a geometric quantity that measures the maximal width of adaptive valleys. The argument of the proof is based on the analogy of the Poisson-ES with a basic Mutation-or-Selection evolutionary strategy introduced in a previous work.