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

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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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Authors and Affiliations

  1. Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Tehran, Iran

    Mohammad Solgi & Omid Bozorg-Haddad

  2. Department of Geography, University of California, Santa Barbara, CA, 93106, USA

    Hugo A. Loáiciga

Authors
  1. Mohammad Solgi
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  2. Omid Bozorg-Haddad
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  3. Hugo A. Loáiciga
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Correspondence to Omid Bozorg-Haddad.

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Solgi, M., Bozorg-Haddad, O. & Loáiciga, H.A. The Enhanced Honey-Bee Mating Optimization Algorithm for Water Resources Optimization. Water Resour Manage 31, 885–901 (2017). https://doi.org/10.1007/s11269-016-1553-x

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  • DOI: https://doi.org/10.1007/s11269-016-1553-x

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