Using Metaheuristics Algorithms (MHAs) to optimize water supply operation in reservoirs: A review

• Main Authors: Almubaidin, Mohammad Abdullah Abid, Ahmed, Ali Najah, Sidek, Lariyah Bte Mohd, Elshafie, Ahmed
• Format: Article
• Published: Springer 2022
• Subjects: QA Mathematics; QA75 Electronic computers. Computer science; TP Chemical technology
• Online Access: http://eprints.um.edu.my/40993/

The optimization of the operation of reservoirs is one of the complex problems in terms of non-linear problems, large numbers of decision variables, and multiple constraints that are difficult to simulate and find solutions to. Researchers have tested several metaheuristics algorithms (MHAs) in the field of water resources and use them to optimize the operation of reservoirs for multiple purposes, the most important of which is to reduce the water deficit in reservoirs using these algorithms and their adoption by decision-makers. The methods of optimization of the operation of the reservoirs vary according to their objectives, the type of reservoir, or the used algorithm. The paper presents the latest studies that dealt with the use of MHAs to optimize the operation related to water supply for the reservoirs by minimizing the losses between release and the water demand from the reservoirs or increase the utilization of the water released from the dams. In addition to studying the basis of the work of these algorithms and their advantages and disadvantages when applied to optimizing operation in some reservoirs. And the effectiveness of developing algorithms to increase their efficiency in solving optimizing problems, either by modifying algorithms or integrating multiple algorithms (hybrid algorithms). The results showed the clear development and high effectiveness in the use of MHAs with different methods based on nature and stochastic in solving problems related to the optimizing operation in various reservoirs by reducing the water deficit in them and evaluating the good performance of these algorithms through different performance indicators. So, we recommend using algorithms that differ in the way they work and categorize them in future research, whether they are new algorithms or old algorithms developed to determine the appropriate algorithms for the nature of these reservoirs, in addition to including different types of reservoirs, studying them, and applying algorithms to solve water problems in them.