Understanding measure-driven algorithms solving irreversibly ill-conditioned problems
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Publication:6137182
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
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)
Cites Work
- Unnamed Item
- Unnamed Item
- An agent-based model of hierarchic genetic search
- Knowledge incorporation in evolutionary computation
- An agent-oriented hierarchic strategy for solving inverse problems
- Towards an analytic framework for analysing the computation time of evolutionary algorithms
- Modeling genetic algorithms with Markov chains.
- Handbook of global optimization. Vol. 2
- Local search methods for the solution of implicit inverse problems
- A hybrid method for inversion of 3D DC resistivity logging measurements
- Multimodal optimization by means of evolutionary algorithms
- Foundations of global genetic optimization. With contribution by Henryk Telega.
- Multi-deme, twin adaptive strategyhp-HGS
- A problem in the optimal design of networks under transverse loading
- Stochastic global optimization methods part I: Clustering methods
- Markov Chains
- Inverse Problem Theory and Methods for Model Parameter Estimation
- The island model as a Markov dynamic system
- Inverse problems for partial differential equations