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The standard cuckoo search algorithm (SCSA) is an intelligent population optimization algorithm, which is also a heuristic search algorithm. The advantages of the SCSA (such as its convenient operation, heuristic searching, etc.) make it easy to find an optimal solution and maintain a wide searching range. However, the SCSA also has some drawbacks, such as long searching time, and the ease of falling on a local optimum. In order to solve the problems existing with SCSA, in this paper, an improved standard cuckoo search algorithm (ISCSA) was studied, which includes chaotic initialization and a Gaussian disturbance algorithm. As a case study, taking economic, social and ecological benefits as the objective function, multi-objective water resources optimal allocation models were constructed in Xianxiang Region, China. The ISCSA was applied to solve the water allocation models and a multi-objective optimal water supply scheme for Xinxiang region was obtained. Water resources optimal allocation schemes for the planning level year (2025) for 12 water supply sub-regions were predicted. A desirable eco-environment and other benefits were achieved using the studied methods. The results show that the ISCSA has obvious advantages in the solution of water resources optimal allocation and planning. HIGHLIGHTS The improved standard cuckoo search algorithm (ISCSA) was studied to overcome the disadvantages of the standard cuckoo search algorithm (SCSA);; The superiority of the ISCSA algorithm was tested and comparisons were made among different functions;; A typical region of China was selected and multi-objective water resources optimal allocation models were constructed and solved using ISCSA;; Desirable results were achieved by using the studied methods.;
The standard cuckoo search algorithm (SCSA) is an intelligent population optimization algorithm, which is also a heuristic search algorithm. The advantages of the SCSA (such as its convenient operation, heuristic searching, etc.) make it easy to find an optimal solution and maintain a wide searching range. However, the SCSA also has some drawbacks, such as long searching time, and the ease of falling on a local optimum. In order to solve the problems existing with SCSA, in this paper, an improved standard cuckoo search algorithm (ISCSA) was studied, which includes chaotic initialization and a Gaussian disturbance algorithm. As a case study, taking economic, social and ecological benefits as the objective function, multi-objective water resources optimal allocation models were constructed in Xianxiang Region, China. The ISCSA was applied to solve the water allocation models and a multi-objective optimal water supply scheme for Xinxiang region was obtained. Water resources optimal allocation schemes for the planning level year (2025) for 12 water supply sub-regions were predicted. A desirable eco-environment and other benefits were achieved using the studied methods. The results show that the ISCSA has obvious advantages in the solution of water resources optimal allocation and planning. HIGHLIGHTS The improved standard cuckoo search algorithm (ISCSA) was studied to overcome the disadvantages of the standard cuckoo search algorithm (SCSA);; The superiority of the ISCSA algorithm was tested and comparisons were made among different functions;; A typical region of China was selected and multi-objective water resources optimal allocation models were constructed and solved using ISCSA;; Desirable results were achieved by using the studied methods.;
Multi-objective water resources optimum allocation scheme based on an improved standard cuckoo search algorithm (ISCSA)
Ke Zhou (author)
2022
Article (Journal)
Electronic Resource
Unknown
multi-objective optimization model , improved standard cuckoo search algorithm (iscsa) , standard cuckoo search algorithm (scsa) , water resources optimal allocation scheme , Water supply for domestic and industrial purposes , TD201-500 , River, lake, and water-supply engineering (General) , TC401-506
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