Study On Scheduling And Optimization Of Parcel Post Automated Warehouse And Intelligent Control For Stack Crane

Automated warehouse is complex field that integrates material handling, computer controlling, management and so on. It is paid more and more attention, because it is of saving labor force, decreasing logistics costs. It is necessary part in factory logistics, flexible manufacture material and computer integral manufacture system, and applied in modern material flow system, traffic and transport wider and wider. If the performance of whole automated warehouse is ensured optimum, the sub-systems must be scheduled and run very well, that is, the scheduling problems of automated warehouse. Moreover it has become a very important research subjection studied by researcher in china and abroad.In the paper, the situation and method of scheduling problem studied of automated warehouse are surveyed completely. The problems of automate guide vehicle transport and stack crane picking order are analyzed deeply in parcel post automated warehouse, basic mathematic model of scheduling is set up. The conception and method of online scheduling in parcel post automated warehouse are put forward, that is dynamic scheduling problem, which is equal to solve online traveling salesman problem. On the basis of mentioned above, an improving genetic algorithms to solve this problem is put forward. Improving genetic algorithms, 3-opt heuristic and first input first output is simulated separately in computer by MatLab, and compared completely. The result of experiment shows that improving genetic algorithms can be used to obtain solution of two kinds of scheduling problems in parcel post automated warehouse, stability is strong, and the speed converging to optimum is higher. This result to improve the efficiency of scheduling, and will benefit practical engineering.Furthermore, because the three grades decelerate control method, which is used widely, in stack crane control in china has some shortcoming, two RBF neuron network applied in position error study and dot position control is put forward. Because neuron network is of self-study, emendation and modification can be achieved in control and can remedy the shortcoming caused by shortage of sample. The result of simulation experiment shows that the speed control rule is of strong adaptable, high-speed response, accuracy position and no speed overshoot.