Ergodicity in Parametric Nonstationary Markov Chains: An Application to Simulated Annealing Methods

DOI10.1287/opre.35.6.867zbMath0639.60071OpenAlexW2061968742MaRDI QIDQ3780216

Shoshana Anily, Awi Federgruen

Publication date: 1987

Published in: Operations Research (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/cac62d7df8817f163694a4e59c30ae9a8f31e435

zbMATH Keywords

simulated annealingstrongly ergodicweakly ergodicmethods for combinatorial optimization

Mathematics Subject Classification ID

Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (7)

Theory of genetic algorithms. II: Models for genetic operators over the string-tensor representation of populations and convergence to global optima for arbitrary fitness function under scaling ⋮ Simulated annealing with extended neighbourhood ⋮ CONVERGENCE OF GENETIC EVOLUTION ALGORITHMS FOR OPTIMIZATION ⋮ On the Ergodicity of Slow-Varying Nonstationary Markov Chains ⋮ A controlled search simulated annealing method for the single machine weighted tardiness problem ⋮ Simulated annealing with asymptotic convergence for nonlinear constrained optimization ⋮ Quantum annealing learning search for solving QUBO problems

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