Multi-objective models must be built to optimise the use of water supplies. In this study, the performance of the farmland fertility algorithm (FFA) and that of the Harris hawks optimisation (HHO) algorithm were evaluated and compared with each other to solve the two-objective problem of optimal operation of the Golestan dam reservoir under baseline (April 2006 to October 2018) and climate change conditions (April 2021 to October 2033) in Golestan Province, Iran. The operation rules were extracted by minimising vulnerability and maximising reliability indices under both conditions. The results showed that when considering a constant value of the reliability index (i.e. 80%), the rate of vulnerability changes in the multi-objective FFA (Moffa) is lower than that of the multi-objective HHO (Mohho) algorithm. Therefore, Moffa has performed better than the Mohho algorithm in the optimal operation of the Golestan dam reservoir under both baseline and climate change conditions. On the other hand, the comparison of the optimum rules obtained under the baseline and climate change conditions showed that supplying the water demands would be more concordant with the optimum rules under climate change conditions in both optimisation algorithms. Therefore, the Golestan dam reservoir could perform better under climate change conditions in the case of using both the mentioned algorithms.

中文翻译：

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单水库大坝系统优化运行的元启发式算法比较

必须建立多目标模型来优化供水的使用。本研究对农田肥力算法（FFA）和哈里斯鹰优化（HHO）算法的性能进行了评估和对比，以解决基线下Golestan大坝水库优化运行的两个目标问题（ 2006 年 4 月至 2018 年 10 月）和伊朗 Golestan 省的气候变化条件（2021 年 4 月至 2033 年 10 月）。通过在两种情况下最小化脆弱性和最大化可靠性指标来提取操作规则。结果表明，当考虑可靠性指标为常数值（即80%）时，多目标FFA（Moffa）算法的脆弱性变化率低于多目标HHO（Mohho）算法。所以，Moffa 在 Golestan 大坝水库在基线和气候变化条件下的优化运行中表现优于 Mohho 算法。另一方面，基线和气候变化条件下得到的最优规则的比较表明，在两种优化算法中，供给需水量与气候变化条件下的最优规则更加一致。因此，在使用上述两种算法的情况下，Golestan 大坝水库可以在气候变化条件下表现更好。基线和气候变化条件下获得的最优规则的比较表明，在两种优化算法中，供应水需求将与气候变化条件下的最优规则更加一致。因此，在使用上述两种算法的情况下，Golestan 大坝水库可以在气候变化条件下表现更好。基线和气候变化条件下获得的最优规则的比较表明，在两种优化算法中，供应水需求将与气候变化条件下的最优规则更加一致。因此，在使用上述两种算法的情况下，Golestan 大坝水库可以在气候变化条件下表现更好。