Crynodeb
Performance analysis of randomised search heuristics is a rapidly growing and developing field. We contribute to its further development by introducing a novel analytical perspective that we call unlimited budget analysis. It has its roots in the very recently introduced approximation error analysis and bears some similarity to fixed budget analysis. The focus is on the progress an optimisation heuristic makes towards a set goal, not on the time it takes to reach this goal, setting it far apart from runtime analysis. We present the framework, apply it to simple mutation-based algorithms, covering both, local and global search. We provide analytical results for a number of simple example functions for unlimited budget analysis and compare them to results derived within the fixed budget framework for the same algorithms and functions.
Iaith wreiddiol | Saesneg |
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Teitl | GECCO 2019 Companion |
Is-deitl | Proceedings of the 2019 Genetic and Evolutionary Computation Conference |
Cyhoeddwr | Association for Computing Machinery |
Tudalennau | 427-428 |
Nifer y tudalennau | 2 |
ISBN (Electronig) | 9781450367486 |
Dynodwyr Gwrthrych Digidol (DOIs) | |
Statws | Cyhoeddwyd - 13 Gorff 2019 |
Digwyddiad | GECCO 2019: The Genetic and Evolutionary Computation Conference - Prague, Y Weriniaeth Tsiec Hyd: 13 Gorff 2019 → 17 Gorff 2019 https://gecco-2019.sigevo.org |
Cyfres gyhoeddiadau
Enw | Proceedings of the Genetic and Evolutionary Computation Conference |
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Cynhadledd
Cynhadledd | GECCO 2019: The Genetic and Evolutionary Computation Conference |
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Gwlad/Tiriogaeth | Y Weriniaeth Tsiec |
Dinas | Prague |
Cyfnod | 13 Gorff 2019 → 17 Gorff 2019 |
Cyfeiriad rhyngrwyd |