Backtracking Search Optimization Algorithm For Navigation Co-scheduling Of The Three Gorges Dam And Gezhouba Dam

The Three Gorges-Gezhou Dam water conservancy hub is the important part of "golden waterway" of China's Yangtze River. Since the implementation of the unified dispatch and management as a whole, putting the navigation capacity to good use will bring great economic benefits for China's shipping of the Yangtze River. With the rapid development of economy, ships over the two dams gradually increase, and the operation of the two dams increases heavy. Therefore scientific dispatch and organization, optimizing the matching operation of the lock have important practical significance.This paper analyses the navigation co-scheduling system of the Three Gorges-Gezhou Dam, considering some constraints of thenavigation process, establishes multi-objective mathematical model by taking the whole of the product of ship waiting time and weight, the whole room area utilization ratio maximization as the objective function minimization. The paper uses two kinds of solution for the multi-objective problem, the first is converting the multi-objective problem into single objective problem by reasonable weight, and doing research combined with the optimization algorithm. The other is optimizing multiple objectives simultaneously by using parallel optimization algorithm. In order to meet the demand for the two aspects, this paper makes some improvements on backtracking search algorithm. The improvements are as follows:(1) First, in order to solve the single objective optimization problem, this paper improves backtracking search algorithm in two aspects against bad local searching ability and slow convergence. First of all, on the choice strategy, this paper reserves the best individuals based on reserving the memory of history population, to lead the population to the optimal solution direction. without losing its diversity in the same time. Secondly, on the cross strategy, this paper makes the crossover strategy of real coded of genetic algorithm and the basic backtracking search algorithm in parallel, selected randomly to accelerate the convergence speed and avoid falling into local optimum to reserve the advantage of mining capacity to the outside world.(2) Secondly, for solving the multi-objective problem, this paper develops a non-dominated sorting backtracking search algorithm(NSBSA-IC), by drawing lessons from the non-dominated sorting and crowding operator and combining with the improved backtracking search algorithm, and tests it by using of several classical test functions, which indicates that this algorithm is suitable for solving high coupling and strong-coupling multi-objective optimization problem.In order to verify the validity of IBSA algorithm and NSBSA-IC algorithm on the navigation co-scheduling problem, this paper applies a plan period of data of the ship randomly chosen for simulation calculation. The results show that the algorithm is feasible and effective, and has a better result than other algorithmsin the case of satisfy all constraints. Therefore, the algorithm is feasible and effective when used to solve the Navigation Co-scheduling problem of the Three Gorges-Gezhou Dam. In order to better adapt to the current traffic scheduling situation of the two dams, this paper studied the two dams under surplus, general, insufficient three shipping capacity states. And the test results show that, IBSA algorithm is feasible and effective in solving the problem under the three states.