A multi-constrained heuristic progressive optimality algorithm for flood control operation

The decision maker's experience and knowledge on judgments have a significant influence on the actual flood control operation. In this paper, the decision maker's experience on flood control pre-discharge dispatching and on the required persistent state of releasing flood waters are considered as constraints , and a multi-constrained heuristic progressive optimality algorithm (MHPOA) for flood control operation is thus proposed. In the MHPOA, the general operation rule for flood releasing is seen as heuristic information, which controls the operation of increasing or decreasing discharge rates by judging the variation tendency of inflow and reservoir level. The heuristic information is combined with the progressive optimality algorithm to searching for the optimal operation of flood control with the objective of maximal flood peak reduction. The proposed algorithm is tested for 5 different scenarios designed for optimizing the flood control operation in the Shuikou reservoir. The result shows that the MHPOA is able take a full account of decision maker's experience and knowledge on judgments, reduce the refill risk caused by the issue of too low reservoir levels in the pre-discharge period, avoid the fluctuation of discharge, and obtain the satisfactory solution.