ACM Transactions on Mathematical Software (TOMS)
On the convergence rate of annealing processes
SIAM Journal on Control and Optimization
Parallel simulated annealing techniques
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Weak convergence of Markov chain sampling methods and annealing algorithms to diffusions
Journal of Optimization Theory and Applications
Pure adaptive search in global optimization
Mathematical Programming: Series A and B
Evolving artificial intelligence
Evolving artificial intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy
Proceedings of the 3rd International Conference on Genetic Algorithms
Fine-Grained Parallel Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Large Derivations, Evolutionary Computation and Comparisons of Algorithms
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
A study of parallel evolution strategy: pattern search on a GPU computing platform
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
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Simulated annealing and single-trial versions of evolution strategies possess a close relationship when they are designed for optimization over continuous variables. Analytical investigations of their differences and similarities lead to a cross-fertilization of both approaches, resulting in new theoretical results, new parallel population-based algorithms, and a better understanding of the interrelationships.