Analysis On Adaptability Of Task Scheduling Algorithm And Parameter Configuration For Shuttle-based Storage And Retrieval System

The shuttle-based storage and retrieval system is an emerging automatic storage and sorting system.Because there are multiple shuttles operating in parallel in the system,the efficiency and flexibility of the system are greatly improved compared to traditional automated warehouses.It has gradually become a hot spot in industrial applications and theoretical research.At the same time,the shuttle-based storage and retrieval system is also a complex collaborative operation system,and the scheduling strategy and various parameter settings of automatic equipment will affect the performance of the system.This article focuses on the study of the system's outbound task scheduling and parameter configuration issues,and is committed to obtaining optimized equipment scheduling schemes and system parameter setting schemes.On the one hand,it provides a theoretical basis for solving the same type of problems,and can be combined with practical applications,Improve equipment utilization rate and order fulfillment rate,help enterprises reduce costs and increase efficiency.First,it analyzes the operation process of the shuttle storage system,classifies and calculates the various service hours of the shuttle and lift,and lays a theoretical foundation for the analysis of the scheduling tasks and parameter setting problems of the outbound warehouse.Then,for the scheduling task of the outbound task in the single-instruction operation mode with a fixed time window,the minimum total outbound time is taken as the optimization goal,considering the uniqueness and continuity of the task,the cooperative operation of the shuttle and the lift,etc.The equation establishes an accurate outbound task scheduling model.For the solution of the model,based on the analysis of the solving mechanism and advantages and disadvantages of the mathematical programming solver Gurobi,two meta-heuristic hybrid algorithms are designed-the improved ant colony algorithm TS-ACO and the fusion genetic algorithm that integrate tabu search The ant colony algorithm GA-ACO also innovatively proposes a heuristic algorithm and Gurobi fusion solution,which expands the new idea of obtaining accurate solutions to problems quickly.After verifying the accuracy of the model,the solution bottlenecks of the three algorithms are analyzed through multiple sets of examples,and the adaptability of the problem scale and solution is studied,which provides guidance for algorithm selection for efficient solution of task scheduling problems,which is conducive to improve the efficiency of system delivery.Finally,further consider the problem of system parameter configuration in the dual-command operating mode,using the state analysis method to construct the corresponding average service time model of the shuttle and lift,comprehensively considering the impact of energy recovery technology on the actual energy consumption of the system,and establishing the task The average energy consumption and energy regeneration model of the system,combined with the system operation,developed a total cost model of the system that considers carbon emissions factors,comprehensively analyzed the system performance from three dimensions,and developed a system.performance calculation tool to quickly and easily obtain the performance of the system.The validity of the mean service time model was verified through simulation experiments,and the error did not exceed 7%.The effects of shelf configuration parameters and equipment operating parameters on the mean service time of equipment,mean energy consumption of tasks,and system cost were also studied.Balance is the goal,optimize the equipment operating parameters under different shelf configurations,and provide a reference for enterprises to rationally configure system parameters.