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Erschienen in: Water Resources Management 3/2017

06.12.2016

The Enhanced Honey-Bee Mating Optimization Algorithm for Water Resources Optimization

verfasst von: Mohammad Solgi, Omid Bozorg-Haddad, Hugo A. Loáiciga

Erschienen in: Water Resources Management | Ausgabe 3/2017

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Abstract

Evolutionary and meta-heuristic algorithms are widely used to solve water resources optimization problems. In this context, the honey bee mating optimization (HBMO) algorithm, inspired by the mating ritual of honey bees, is a reliable and efficient algorithm. The HBMO algorithm is modified in this work leading to the Enhanced HBMO (EHBMO) algorithm. The EHBMO is then applied to solve several unconstrained/constrained mathematical benchmark functions and a multi-reservoir problem. The performance of the EHBMO is compared with those of the elitist genetic algorithm (EGA) and the HBMO algorithm. The results show that the EHBMO achieves a better solution in a smaller number of functional evaluations and with less variance of results about global optima in comparison with the EGA and the HBMO algorithm.

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Metadaten
Titel
The Enhanced Honey-Bee Mating Optimization Algorithm for Water Resources Optimization
verfasst von
Mohammad Solgi
Omid Bozorg-Haddad
Hugo A. Loáiciga
Publikationsdatum
06.12.2016
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 3/2017
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-016-1553-x

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