The Research On Optimization Of In Multiple I/O-points Automated Warehouse

Automated Storage and Retrieval System(AS/RS)is an excellent product of automation and rapid development of logistics,as the key link in the process of transportation and logistics, it is the complexity of integrated automation system of handling storage and distribution in one. With the rapid development of logistics industry, higher requirements are put forward for the AS/RS. This paper is mainly introduction and research from these two aspects.(1)The logistics as the research background, the type and structure of AS/RS are described in the paper, especially on location assignment and scheduling optimization, and on these two aspects are introduced in detail in the dissertation.(2)The dissertation introduced genetic algorithm and operators influenced the quality of solution,and the shortcomings of the genetic algorithm are described in the process of solving, pointed out that solutions diversity poor and premature convergence and search accuracy is not enough in the evolution process, it will appear the problem of diversity poor. According to the above problems, the paper uses logistic curve to adjust the crossover rate and mutation rate so that the operator can meet the requirements of different stages in the evolution process. The experimental results show that the improved LO adaptive genetic algorithm has advantages over the traditional in the stability, convergence speed and diversity of the solution.(3)Compared to the traditional AS/RS,multiple I/O points is a new type one.With high efficiency of storage,it is applied to many occasions, and reasonable scheduling optimization is an effective way. In this paper, the scheduling optimization of multiple I/O points AS/RS is studied. Access to the research of multiple I/O points AS/RS, to minimize the stacker execution time, establisht time model of multiple I/O points AS/RS, use the improved LO genetic algorithm to solve the model, through using of improved crossover and mutation operators to obtain optimal solution of the model. The experimental results show that the proposed model and solving method are able to quickly get good quality solutions. So it can effectively improve the efficiency.(4) Location optimization is to choose suitable location in order to improve the efficiency. Location assignment and scheduling have a close correlation, it is difficult to overall improve efficiency which on the one hand. With its features, we can study from the point of view of integration. Considering the influence of loading and no load condition, the corresponding time model is established. Integrated optimization model is solved by designing two tabu search algorithm. Experimental results show integration optimization model and its solving method can quickly get excellent solution. So it can effectively improve the efficiency of the warehouse.