Drift analysis of mutation operations for biogeography-based optimization

DOI10.1007/s00500-014-1370-1zbMath1359.68267OpenAlexW1992589780MaRDI QIDQ521639

Shuzhi Sam Ge, Yanfen Mao, Hongliang Ren, Weian Guo, Lei Wang

Publication date: 11 April 2017

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-014-1370-1

zbMATH Keywords

evolutionary algorithmdrift analysismutation operatorbiogeography-based optimizationexpected first hitting timemigration operator

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Cites Work

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• Modified projective synchronization of uncertain fractional order hyperchaotic systems
• Evolutionary programming using a mixed mutation strategy
• A real-coded biogeography-based optimization with mutation
• An analysis of the equilibrium of migration models for biogeography-based optimization
• On the analysis of the \((1+1)\) evolutionary algorithm
• A study of drift analysis for estimating computation time of evolutionary algorithms
• Black-box search by unbiased variation
• On the convergence rates of genetic algorithms
• A new approach to estimating the expected first hitting time of evolutionary algorithms
• Hitting-time and occupation-time bounds implied by drift analysis with applications
• Drift analysis and average time complexity of evolutionary algorithms

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