A Markov chain analysis of genetic algorithms with power of 2 cardinality alphabets

DOI10.1016/S0377-2217(96)00121-XzbMath0924.90117OpenAlexW1987074714MaRDI QIDQ1278478

Haldun Aytug, Gary J. Koehler, Siddhartha Bhattacharyya

Publication date: 22 February 1999

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(96)00121-x

zbMATH Keywords

stopping criteriaMarkov chainconvergence rategenetic algorithmtransition probabilitieshigher cardinalityrun time behavior

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Combinatorial optimization (90C27) Stopping times; optimal stopping problems; gambling theory (60G40)

Related Items (5)

A general steady state distribution based stopping criteria for finite length genetic algorithms ⋮ The effect of multiple optima on the simple GA run-time complexity ⋮ Markov chain analysis of self-organizing mobile nodes self-organizing mobile nodes ⋮ New stopping criterion for genetic algorithms ⋮ Genetic algorithm for constrained global optimization in continuous variables

Cites Work

• Modeling genetic algorithms with Markov chains.
• Stopping Criteria for Finite Length Genetic Algorithms
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