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| Titel |
A Diagnostic Assessment of Evolutionary Multiobjective Optimization for Water Resources Systems |
| VerfasserIn |
P. Reed, D. Hadka, J. Herman, J. Kasprzyk, J. Kollat |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250059769
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| Zusammenfassung |
| This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective
evolutionary algorithms (MOEAs) and highlights key advances that the water resources field
can exploit to better discover the critical tradeoffs constraining our systems. This study
provides the most comprehensive diagnostic assessment of MOEAs for water resources to
date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The
diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of
ten benchmark MOEAs for a representative suite of water resources applications addressing
rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based
water supply portfolio planning. The suite of problems encompasses a range of
challenging problem properties including (1) many-objective formulations with
4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4)
discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability
(also called epistasis). The applications are representative of the dominant problem
classes that have shaped the history of MOEAs in water resources and that will be
dominant foci in the future. Recommendations are provided for which modern
MOEAs should serve as tools and benchmarks in the future water resources literature. |
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