Backtracking adaptive search: distribution of number of iterations to convergence

DOI10.1007/s10957-006-9040-9zbMath1112.90105OpenAlexW1963973553MaRDI QIDQ857596

David L. J. Alexander, David W. Bulger, W. P. Baritompa, Graham R. Wood

Publication date: 19 December 2006

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-006-9040-9

zbMATH Keywords

global optimizationconvergence ratessimulated annealingpoint processesadaptive search

Mathematics Subject Classification ID

Search theory (90B40) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (2)

Hesitant adaptive search with estimation and quantile adaptive search for global optimization with noise ⋮ Generating functions and the performance of backtracking adaptive search

Cites Work

• Approximation of the distribution of convergence times for stochastic global optimisation
• Pure adaptive search in global optimization
• Hesitant adaptive search for global optimisation
• Convergence and first hitting time of simulated annealing algorithms for continuous global optimization
• Implementing pure adaptive search with Grover's quantum algorithm
• Expected search duration for finite backtracking adaptive search
• Hesitant adaptive search: The distribution of the number of iterations to convergence
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