Large-scale inter-basin water transfer projects typically manifest the characteristics of multiple water sources

multiple objectives

multiple users

and multiple dimensions

whereas their different water sources

objectives

and water users are often interconnected yet mutually constraining

leading to new challenges in modeling their joint optimal scheduling and solving the problem. This study constructs a new model for water allocation optimization under the reservoirs' dynamic regulation rules

based on a genetic algorithm (GA) framework

and applied in a case study of the Jiaodong Water Transfer Project. We use this model to determine the system's water flow behaviors through accurate water balance simulations

and then design a fitness function via a comprehensive consideration of the constraints and multi-objective requirements of the project. Finally

its updated solutions are adjusted using a reverse correction strategy. To enhance algorithm efficiency

we have developed three key techniques: adopting a phase identification and division method to reduce decision variable dimensionality; determining the optimization adjustment directions based on reservoir regulation rules; and developing an intelligent mechanism for infeasible solution handling. Application of the new model to the transfer project shows a significant improvement on scheduling performance. Compared with the annual operational plan

a full scheduling period scheme raises the minimum water supply reliability at the diversion outlets by 22%

achieving superior water supply outcomes with reduced diversion flow. In the remaining period scheme

the Jihongtan Reservoir achieves a water supply reliability of 74.17%

with a water shortage of 102.2267 million m3 and a water diversion index utilization rate of 98.43%

meeting all the project requirements. This study helps consider and address optimal operation challenges in complex inter-basin water transfer systems.