The Research On Scheduling Optimization In Automated Storage And Retrieval System

With the development of the economy, the physical distribution is more and more takenby the people, and logistics facilities-related issues have become the hot spots. Automatedwarehouse collection of information, storing, managing, integrating,it’s the key to entirelogistics system automation and information. Automated warehouse optimization schedulingdecision the warehouse chain of benefits, also direct influence entire physical distributionsystem movement so the research on scheduling optimization in AS/RS is logistics focus oflearning and attention problems. Research on the issue has important theoretical significanceand practical works.The this article take AS/RS as the object of study, gives the solution to its schedulingproblem,The main task of this thesis is briefly described as follows.First, for the position optimization problem of entering warehouse process, divided theshelf into a sector region by the policy of storage space district,make the cargo partitioncorresponds to the goods species anoptimization of location assignment is established basedon theprinciple of position distribution to elevate the shelf stability and accessefficiency.Based on the problems of NP properties，The article design of the calculation modelby genetic algorithm,it is greatly raised the operation efficiency of the algorithm by usingdistrict matrix coding.It is also avoid the crossover and mutation of chromosomes that are notvalid during.Finally to establish a simulation system based on Matlab, the simulation resultsshow that the accuracy of model and the validity of algorithm.Second, for the position optimization problem of outbound order picking, the pickingstrategy in delivery process is analyzed based on the operation process of automatedwarehouse. The path optimization model is established for the goal of achieving the shortestwalking distance of retrieval machine and transform the model for TSP problem. Finally, asatisfactory solution is obtained by using Ant Colony optimization algorithm.