Understanding measure-driven algorithms solving irreversibly ill-conditioned problems

DOI10.1007/s11047-020-09836-wzbMath1530.90085OpenAlexW3131309474MaRDI QIDQ6137182

Robert Schaefer, Marcin M. Łoś, Jakub Sawicki, MacIej Smołka

Publication date: 1 September 2023

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

Full work available at URL: https://doi.org/10.1007/s11047-020-09836-w

zbMATH Keywords

Markov chain modelingirreversibly ill-conditioned problemsmeasure-driven algorithms

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

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