New Hybrid Optimization Approaches for the Optimal Management of Surface Water Resources Systems

Meta-heuristic algorithms have been successfully used in solving a variety of engineering problems. The optimal operation of multi-reservoirs is one the most complex engineering problem, so there is an increasing need for the development of such algorithms. In this study, a new hybrid algorithm, Symbiotic Organisms Search based on Moth Swarm Algorithm (SOS-MSA), in comparison to three robust algorithms of Fitness-Distance-Balance-based Symbiotic Organisms Search (FDB-SOS) algorithm, Harmony Search (HS) algorithm and Imperialist Competitive algorithm (ICA) were developed for optimal management of surface water resources systems. The Halilrood basin surface water resource system in the Southeast of Iran consisting of Baft, Safarud, and Jiroft dams was considered as the case study. The purpose was to find the best scenario for allocating the water resources among the domestic, environmental, agricultural, and industrial uses in the case study, provided that the drinking water demand being given precedence. The results demonstrated that the new hybrid SOS-MSA algorithm provided the most efficient operation policies in a shortest run time which could supply 88%, 73.63%, and 99.07% of the downstream demands of Baft, Safarud, and Jiroft reservoirs. In addition, the best values of sustainability index (SI) were achieved by SOS-MSA algorithm followed by FDB-SOS algorithm indicating the superior performance of these algorithms over the HS and ICA algorithms in optimal operation of multi-reservoir system.