New stopping criterion for genetic algorithms

DOI10.1016/S0377-2217(99)00321-5zbMath0982.90067MaRDI QIDQ5928454

Haldun Aytug, Gary J. Koehler

Publication date: 28 March 2001

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

zbMATH Keywords

Markov chainsfirst passage timesgenetic algorithmsstopping condition

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Markov and semi-Markov decision processes (90C40)

Related Items (11)

Modifications of real code genetic algorithm for global optimization ⋮ A general steady state distribution based stopping criteria for finite length genetic algorithms ⋮ The multifactor nature of the volatility of futures markets ⋮ The effect of multiple optima on the simple GA run-time complexity ⋮ Modified genetic algorithm-based clustering for probability density functions ⋮ Subset selection in multiple linear regression models: a hybrid of genetic and simulated annealing algorithms ⋮ A new stopping criterion for multi-objective evolutionary algorithms: application in the calibration of a hydrologic model ⋮ A hybrid genetic algorithm with the Baldwin effect ⋮ A stopping criterion for multi-objective optimization evolutionary algorithms ⋮ Terminating evolutionary algorithms at their steady state ⋮ Genetic algorithm for constrained global optimization in continuous variables

Cites Work

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• A Markov chain analysis of genetic algorithms with power of 2 cardinality alphabets
• Modeling genetic algorithms with Markov chains.
• New directions in genetic algorithm theory
• Convergence Criteria for Genetic Algorithms
• Stopping Criteria for Finite Length Genetic Algorithms

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