To address water resources-related management issues, different evolutionary and heuristic algorithms have been developed in recent years. In this paper, a new algorithm is introduced for optimizing the operation of reservoir systems. Specifically, the anarchic society optimization (ASO) algorithm is applied to solve water resources management problems for the first time. In these problems, the operations of a single-reservoir hydropower system (Karun-4 reservoir) and a four-reservoir system with the objective of maximizing the profits of releases are optimized. The objective function values of the ASO algorithm and the genetic algorithm (GA) for Karun-4 reservoir are 1.254 and 1.535, respectively. The objective function value from the ASO algorithm is very close to the global optimum (1.213) from the non-linear programming (NLP). The optimal solution of the ASO algorithm for the four-reservoir system covers 93.88% of the NLP value, while the GA model only accounts for 91.86% of the global optimum, indicating that the ASO algorithm does have better performance. The applications of the ASO algorithm for three benchmark mathematical functions and the single- and multi-reservoir systems and the comparisons with the GA method demonstrate its acceptable performance and applicability to real, complex engineering problems.

You do not currently have access to this content.