Lu: Xingcai Automated Stereoscopic Warehouse Optimization Scheduling Algorithm Research

The scheduling problem of AS/RS has been a hotspot research in recent years, the relatively studies on scheduling problems of Aluminum AS/RS is not sufficient. This thesis has Nan ping Aluminum AS/RS as the research background, Conducts a more in-depth study on access schedu-ling optimization problem of AS/RS.Establishes a mathematical model of the Aluminum AS/RS, pproposes the shortest path optimization algorit-hm and the least turned-out slab stack optimization algorithm. The simul-ation results have demonstrated the effectiveness of the algorithm.The thesis briefly introduces the layout and structure of Nan ping Aluminum AS/RS, establishes the mathematical model of the stacker task scheduling according to its own characteristics.focus on cargo space problem of the Aluminum AS/RS, it proposes the uniform classification storage strategy based on good-cargo coupled allocation, makes the same kind of profiles which can be operated in different stackers come true,and accelerates the speed of enter and out of storage.In the basis of the optimized of cargo space allocation and the certain position of warehouses out-in storage, we put forward a new theory about using a heuristic genetic algorithm to solve the shortest path of cargo’s in-out. We uses the best individual preservative strategy to speed up the algorithm convergence and verified the algorithm’s efficiency through MATLAB simulation. In conclusion, the optimization effect is stronger than the traditional genetic algorithm.According to compare the time can be optimized of stacker shortest path problem and the time of turn-out slap stack problem, the turn-out slap stack optimization is more conducive to improve the efficiency of warehouse operations, so establish a mathematical model for the turn-out slap stack optimization. Combinating the optimal stack selection method based on dynamic stack, we use genetic algorithms to reduce the times of the turn-out slap stack optimization to the least. The optimal stack selection method is to select the least times of the turn-out slap stack in the exchangeable Aluminum group.Using adaptive crossover and mutati-on strategy in order to improve the diversity of the group structure and accelerate the speed of convergence of the genetic algorithm. The examp-le shows that the turn-out slap stack problem of the Aluminum AS/RS can be optimized by the genetic algorithm. This paper can be a guidance for optimize the scheduling system in AS/RS in practice.