Optimal operation of multi-purpose multi-reservoir dams is a challenging problem for dams’ stakeholders and
decision-makers. Optimization algorithms are able to present reliable solutions for such complex problems. This
study compared the capability of 20 state-of-the-art robust meta-heuristic algorithms for determining the optimal
operating policy of Halilrood multi-reservoir system under the three competing operational objectives of water
supply, flood control, and hydropower generation. Before that, the performance of the algorithms in solving two
benchmark problems (the Schaffer problem and the MMF1 problem from the CEC suite) was evaluated. Four
metrics of generational distance (GD), spacing (S), spread (Δ), and maximum spread (MS) were used to compare
the algorithms’ performance in solving the benchmark problems. In addition, four reservoirs performance evaluation
indicators of reliability (Rel), resiliency (Res), vulnerability (Vul), and sustainability index (SI) were used to
ass the algorithms’ performance in solving the real-case Halilrood problem. The results showed that although the
solving capability of each algorithm depends on the nature of the problem, some algorithms were always superior
in solving all three problems (2 benchmark problems and one real case). For the Schaffer benchmark problem,
the MOAHA algorithm with the performance metrics of (GD = 0.00095, S = 0.58155, Δ = 0.20375,
MS = 4.0002) had the best Pareto front in terms of coverage and diversity, and so it was placed at the first rank.
In this problem, the MOCryStAl algorithm with (GD = 0.00141, S = 0.48395, Δ = 1.49467, MS = 3.94799)
placed at the lowest rank. For the MMF1 problem, the MOMA (GD = 0.00751, S = 0.07516, Δ = 0.29519,
MS = 0.99826) followed by the MOAHA (GD = 0.00833, S = 0.07660, Δ = 0.17832, MS = 1.00) had the best
performance, respectively, and the MOFA algorithms was the worst. For the Halilrood real-case problem, the
MOGWO algorithm (with Rel = 83.41, Res = 67.57, Vul = 22.07 and SI = 76.01) followed by the MOAHA algorithm
(Rel = 84.57, Res = 64.71, Vul = 33.60, and SI = 71.41) and the MOMA algorithm (Rel = 79.82,
Res = 66.67, Vul = 21.65, and SI = 74.70) obtained the best ranks in terms of reservoir's performance evaluation
indicators. They could successfully minimize all three objectives of the total deficit, the flood control and
electricity generation indicating the highest performance of these algorithms in the optimization problem. The
Pareto front obtained by these algorithms had better distribution and was closer to the origin of coordinates compared
to the other utilized algorithms. They could favorably supply the total water demand in the Halilrood basin
while increasing the hydropower energy generation up to the power plant capacity at the Jiroft dam. The results
of this study can be applied to the optimal operation of any other multi-reservoir system with conflict in water
demands.