Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e....

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Veröffentlicht in:Environmental modelling & software : with environment data news Jg. 62; S. 271 - 299
Hauptverfasser: Maier, H.R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L.S., Cunha, M.C., Dandy, G.C., Gibbs, M.S., Keedwell, E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D.P., Vrugt, J.A., Zecchin, A.C., Minsker, B.S., Barbour, E.J., Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., Reed, P.M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.12.2014
Elsevier
Schlagworte:
Algorithms
Animal, plant and microbial ecology
Biological and medical sciences
Computational efficiency
Computer programs
computer software
decision making
environmental models
Evolutionary algorithms
Fitness
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Heuristic methods
Landscapes
Metaheuristics
Methods and techniques (sampling, tagging, trapping, modelling...)
Optimisation
planning
Research directions
Review
water distribution
Water resources
Research directions
Evolutionary algorithms
Review
Optimisation
Metaheuristics
Water resources
Status
Water current
Algorithm
Optimization
ISSN:1364-8152
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Zusammenfassung:The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.
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ISSN:1364-8152
DOI:10.1016/j.envsoft.2014.09.013