Research On Route Planning And Task Scheduling Algorithm Of Four-direction Shuttle

E-commerce platform receives orders year by year increase,urgent need more efficient automated warehousing system to meet the market demand.Four-direction shuttle stereoscopic library is widely used in storage system because of its high space utilization rate,flexible shuttle route selection and effective access to goods.This paper takes the Four-direction shuttle developed by Taiyuan FORTUCKY as the object,aiming at the Four-direction shuttle route planning algorithm,task scheduling algorithm and shuttle job scheduling method.In Plant Simulation software,the size of each cargo space cell is equal,and each cargo space is coded and marked according to the number of rows.Based on the idea of raster modeling,the grid map model of Four-direction shuttle stereoscopic library is constructed to provide an environment for subsequent simulation experiments.Aiming at the path planning of Four-direction shuttle,the Geneticunidirectional Dijkstra algorithm is proposed,which satisfies the goal of shortest path distance and shortest walking time.Firstly,the unidirectional Dijkstra algorithm is designed for path planning,and the forbidding set L is added to the Dijkstra algorithm,so that the traversal process of the Dijkstra algorithm is always in the direction of the end,and the path rectangle box with the shortest distance is obtained with the path starting point and ending point as the diagonal.Then,some paths in the rectangular box are randomly selected as the initial population of the genetic algorithm.All path inflection points in the population were extracted for crossover and mutation operation,and the sequence that could not form a path and the path outside the rectangle box were removed.A particle swarm optimization-simulated annealing algorithm was designed for task scheduling of Four-direction shuttle.The simulated annealing algorithm is nested into particle swarm optimization algorithm to solve the problem of local convergence of particle swarm optimization algorithm.The acceleration factor of particle swarm optimization algorithm changes dynamically,which enhances the global search ability of the algorithm in the early iteration period and speeds up the convergence rate in the late iteration period.The cooling rule of simulated annealing algorithm uses linear exponential cooling rule,the temperature drops rapidly in the early stage of iteration to improve the convergence rate of the algorithm,and the temperature drops slowly in the late stage to improve the convergence accuracy of the algorithm.Aiming at the Four-direction shuttle job scheduling,the first come first service and priority method are combined to solve the conflict problem of shuttle.The simulation experiment is carried out in the single and multi-layer of the Four-direction shuttle stereoscopic library of Taiyuan FORTUCKY.The results show that both Genetic-unidirectional Dijkstra algorithm and optimization-simulated annealing algorithm can achieve fast and accurate optimization results.The shuttle job scheduling method combining the first come first serve and priority method can solve the shuttle conflict problem quickly and effectively.The utilization rate of storage system equipment of Four-direction shuttle is improved.