Establishing a stable balance between the amount of recoverable water resources and its demand has always been a great challenge for water managers, which the two main roots of this imbalance can be considered as the natural limitations of available water resources and destructive human activities. With increasing population and on the other hand climate change, which in recent years has affected the level of access to water resources, the optimization of reservoirs operation as the main surface water containment systems has become an increasingly important issue in water resource management. Zayandehrood Dam as the most important surface water utilization system located in Zayandehrood catchment, which due to climate change, droughts and lack of proper and comprehensive management in recent years has faced many problems in estimating the water demands of regional applicants in various sectors, has been selected as a case study of the present research, which requires optimization under new and effective methods in order to adapt to climate change. Meta-heuristic algorithms, which have been widely used in the field of water systems management due to their high power in finding good enough solutions in a reasonable amount of time for complex real-world problems, have been used in optimizing current dam performance. The AAGSA, which is a modified version of the Gravitational Search Algorithm (GSA), has been implemented as the research innovation on the study reservoir and its optimization results have been compared with GSA under both historical and future periods. The results showed that under the 13-year historical period from 1385 to 1398 solar years and also under the future 13-year period from 1399 to 1412, as expected, the improved algorithm (AAGSA) due to the greater global search power and speed offered a better optimal solution in a shorter runtime (Approximately 78% less than GSA runtime). The results of 30 performances showed that due to the weak performance of GSA algorithm in fulfilling the constraint related to the optimal storage (450 MCM) at the end of each water year, GSA resulted in higher amounts of monthly storage and spill volumes compared to AAGSA and observed values. However, in terms of the percentage of water demand supply, GSA represented only 2% more than the observed value and in terms of performance criteria and sustainability index, it showed the better results than the observed values; But AAGSA performed better in all fields than the GSA algorithm and the observed values. AAGSA algorithm with supplying 89% of water demand (8.4% better than GSA and 9.4% better than observed value) and with fuzzy sustainaility index of 94.6% (24% better than GSA and 50% better than observed value) showed its superiority in the historical period. After testing the algorithms in the historical period, with the help of LARS-WG and HEC-HMS model outputs from previous researches, the reservoir inputs in the future period under RCP4.5 climate change scenario which, despite of slight differences, was more critical than RCP2.6 and RCP8.5 scenarios entered the algorithms. Since the total volume of 13-year inflow to the dam were higher than the estimated water demand volume of the whole period compared to the past, the results of 30 performances showed that both algorithms in terms of percentage of supply and performance criteria of the reservoir in the future better than before (computational water supply percentage by AAGSA was 6% better than this amount in the past). AAGSA again showed better performance in all fields than the GSA algorithm. AAGSA proved its superiority over the main algorithm in the future period by providing 95% of water demand (10.8% better than GSA) and with 89% sustainability index (20.1% better than GSA). In general, AAGSA compared to GSA improved the sustainability index of Zayandehrood Dam in the historical period and in the future period by 34.5 and 29%, respectively, and the optimal fit function by 92 and 84.2%, respectively. Keywords: Reservoir operation, Upstream catchment of Zayandehrood dam, Climate change, Fuzzy sustainability index, HEC-HMS, AAGSA