Shafii - Department of Civil Eng, Iran University of Science and Technology
Bozorg Haddad - Department of Civil Eng, Iran University of Science and Technology
Afshar - Department of Civil Eng, Iran University of Science and Technology

Over the last decade, evolutionary and meta-heuristic algorithms (EAs) have been extensively used as search and optimization tools in various engineering problems. Honey bees mating optimization (HBMO) algorithm in which the search algorithm is inspired by the process of real honey-bees marriage has been recently employed as search and optimization methods to solve some mathematical and water resources problems. There have been some uses of HBMO in reservoir operation optimization. In this paper, honey-bees mating optimization algorithm (HBMO) is improved and tested with reservoir operation optimization problem, along with the comparison with a well developed GA model. To test the performance of the improved algorithm, after conducting some sensitivity analyses, optimization of a single reservoir operation as a constrained real valued problem was investigated. It has been demonstrated that improving HBMO algorithm provides more robust and acceptable solutions in reservoir operation optimization problem. It was shown that the performance of the improved model is quite comparable with the results of well developed GA. The results achieved indicate that there could be a good potential in application of HBMO to multi-reservoir operation optimization problems, where the objective function is complex and some other classical techniques are difficult to apply.

Flood Optimization, HBMO algorithm, Reservoir Operation, Genetic Algorithm