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

被引：18
|
作者：
Solgi, Mohammad [1 ]
Bozorg-Haddad, Omid [1 ]
Loaiciga, Hugo A. [2 ]
机构：
[1] Univ Tehran, Fac Agr Engn Technol, Dept Irrigat Reclamat Engn, Coll Agr Nat Resources, Tehran, Iran
[2] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
来源：
WATER RESOURCES MANAGEMENT | 2017年 / 31卷 / 03期
关键词：
Enhanced honey-bee mating optimization (EHBMO); Honey-bee mating optimization (HBMO); Elitist genetic algorithm(EGA); Multi-reservoir optimization; Heuristic search; SYSTEM;
D O I：
10.1007/s11269-016-1553-x
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
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.
引用
收藏
页码：885 / 901
页数：17
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