
doi: 10.4314/wsa.v39i2.17
Contemporary reservoir systems often require operators to meet a variety of goals and objectives; these in turn frequently complicate water management decision-making. In addition, many reservoir objectives have non-linear relationships and are therefore difficult to implement using traditional optimisation techniques. A practical application of the marriage in honey bees optimisation (MBO) algorithm is being utilised for Karkheh multi-reservoir system, south-western Iran, where supplying irrigation water for agricultural areas and maintaining a minimum in-stream flow for environmental purposes is desired. Optimal monthly reservoir release information by MBO is highlighted and the results compared to those of other evolutionary algorithms, such as the genetic algorithm (GA), ant colony optimisation for continuous domains (ACOR), particle swarm optimisation (PSO) and elitist-mutation particle swarm optimisation (EMPSO). The results indicate the superiority of MBO over the algorithms tested.Keywords: non-linear optimisation, multi reservoir system, honey bee mating optimisation algorithm, evolutionary algorithms, meta-heuristic algorithms
honey bee mating optimisation algorithm, non-linear optimisation, multi reservoir system, honey bee mating optimisation algorithm, evolutionary algorithms, meta-heuristic algorithms, non-linear optimisation, evolutionary algorithms, meta-heuristic algorithms, multi reservoir system
honey bee mating optimisation algorithm, non-linear optimisation, multi reservoir system, honey bee mating optimisation algorithm, evolutionary algorithms, meta-heuristic algorithms, non-linear optimisation, evolutionary algorithms, meta-heuristic algorithms, multi reservoir system
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