In this paper, an application of the Jaya Algorithm (JA) is presented, to develop an operation optimization model for the Mula reservoir, located on the upper Godavari Basin, in India. The mentioned algorithm is a relatively new optimization technique, which is algorithm-specific and parameterless. In JA, there is no need for algorithm-specific parameter tuning, unlike with other heuristic techniques. To test its applicability, the model performance has been compared with that of other models for hypothetical four reservoir system studies available in the literature. Simulations for hypothetical four reservoir system have proven that JA is a better solution for a number of Function Evaluations when compared with the results obtained by means of other evolutionary methods such as Genetic Algorithms, Particle Swarm Optimization, Elitist Mutated Particle Swarm Optimization, and Weed Optimization Algorithm models reported in previous studies. Simulations have been carried out for real time operation of the Mula reservoir, and have revealed its superior performance when comparing the water releases proposed by it and the ones proposed by existing policy. Hence, from the two case studies presented, it can be concluded that the JA has potential in the field of reservoir operation and can be further explored to operation optimization of existing multi-reservoir system, with lower computations.Sustainability 2020, 12, 84 2 of 21 alternative to meet the present and future water requirements. Many researchers have been working towards rational approaches to allot the water very optimally in every essence. Many approaches can be found in the literature, such as can be read in in every essence; vagaries of approach have been commended in the literature with excellent opinions regarding the distribution of resources [2].The techniques suggested and implemented in reservoir operation studies are chance constrained Linear Programming (LP) by [3], in which multi-purpose reservoir operation optimization was carried out with the aim of maximization of hydropower generation and fulfillment of irrigation requirements according to the reliability level. The nonlinear power production function was linearized and a solution was obtained in the range of the specified tolerance. In a similar way, a multi-purpose reservoir operation optimization was carried out by using Non-Linear Programming (NLP) in [4] for the Koyna dam, Maharashtra, India. Dynamic Programming (DP) [5] was implemented in the integration with fuzzy rules and simulation studies to generate the general operating policies for Dez and Karoon reservoirs in Iran. Ant Colony Optimization (ACO) was implemented for the reservoir operation optimization of the Dez reservoir system, Iran, in [6], and resulted in a global optimal solution although the tuning of parameters was recommended as the model is parameter sensitive. The application of the Bat Algorithm (BA) to the Karoun-4 reservoir system in Iran and to another hypothetical reservoir system showed the merits of the BA over o...

Based on the current water crisis scenario, effective water resources management can play an essential role. Reservoir operation optimization is part of water resources management. Reservoir operation optimization is difficult as it involves a large number of variables and constraints to achieve this goal. The present study aims at exploring the performance of recently developed heuristic algorithms—Rao algorithms as applied to the reservoir operation studies for the first time. Rao algorithms are metaphor-less algorithms that require only basic parameters—population size and function evaluations. In the present study, Rao algorithms have been applied to two case studies: discrete four-reservoir operation system problem and continuous four-reservoir operation system problem (benchmark problems) for the assessment of their performance vis-à-vis other algorithms from the literature. The results showed that the Rao-1 algorithm provided the optimal solution with the least function evaluations when compared to Rao-2, Rao-3, and other algorithms applied in the past to the same benchmark problem. Consequently, the Rao-1 model is found to be superior to these approaches by taking less computational time. Hence, the Rao-1 algorithm can be considered suitable for application to reservoir operation optimization problems.