| Ant Colony Algorithm is a new bionic optimization algorithm. It has many merits such as mechanism of plus-feedback parallelization, strong robustness, excellent distributed computational mechanism and ease of integration with other methods.Ant Colony Algorithm has gradually become a hot research at home and abroad, because of it has shown its excellent capability and huge developing potential in solving many complicated optimization problems. However, it needs longer searching time than others and tends to precocity and stagnation in some sutation, which are obstacles to solve large-scale complex actual schedule problem. Aming at these vices, this research will put forword ant colony algorithm with division-cooperation of labor and sort-weight and apply it in the actual productive optimization of unloading schedule of port coal.Firstly, this paper detailed analysis of the shortcomings and insufficience of the basic ant colony algorithm, combines the working of the actual ant colony system, and presents the ant colony algorithm with division-cooperation of labor and sort-weight. The new algorithm uses an approach of division-cooperation of labor, and sets different pheromone contral mechanism; it adds weight values respectively in the initialization of pheromone, the choice of transition probability and the pheromone update mechanism; what's more, the pheromone is restricted.Secondly, the article combines with the ideal of the symmetrical design set the parameters of the improved algotihms rationally. It shows the validity of the parameters by imitate experiment. Whereafter, the example of the travel saler problem is used to do imitate experiment for ant colony algorithm with division-cooperation of labor and sort-weight, and proves the new optimization algorithm not only to enhance the searching precision and speed, and in a certain extent avoid premature convergence.Lastly, the new ant colony algorithm presented combining with G&T algorithm is applied in the actual problem of the pot coal unloading scheduling problem. After the actual research, the problems in the port of coal unloading scheduling are analyzied, and the corresponding scheduling model is established. The ideas of using ant colony algorithm to solve combinatorial optimization problems and Job-shop scheduling problem are used to solve the combinatorial optimization of coal unloading scheduling. By comparing a large number of Simulation examples, it's proved that the capacity of the ant colony optimization algorithm to solve the problems of port coal unloading job scheduling port is better than the primary actual scheduling method. |