Research On Optimization Algorithm For Autonomous Carriage Dispatching Efficiency Of Terminal

The large-scale and complex layout of the civil aviation airport terminal has led to cumbersome business operations and long travel distances for passengers,which greatly reduces the aviation travel experience.For this reason,the autonomous transportation robot in the terminal building developed for this purpose can quickly deliver passengers in need Destinations such as the boarding gate.Among them,multiple robots work together under the premise of meeting passenger service needs,and the lowest consumption is one of the key issues that need to be solved.In response to the above problems,the autonomous robot transport service in public environments such as terminal buildings was studied,a new type of robot group scheduling model—demand-time-space-energy consumption scheduling model was constructed,and a global fast convergence ant for task scheduling optimization was designed.-Sparrow optimization algorithm.First,a demand-time-space-energy consumption model is constructed.The general passenger boarding tolerance and waiting probability model and a man-machine Manhattan distance model based on a hexagonal solution are studied;and the passenger waiting time and the energy consumption of the robot group are used as optimization indicators,and the construction is based on the passenger demand and waiting time and considers the man-machine Multi-objective scheduling efficiency optimization model for location and robot group energy consumption.Secondly,a variety of intelligent optimization algorithms are designed to solve the demand-time-space-energy consumption scheduling model.The basic principles of each algorithm are studied,combined with the inherent discrete characteristics of the robot group scheduling model,the sequence of the robot ID sequence and the order of passengers are integer-coded;the steps and system flow for solving the robot group scheduling model are given,combined with reality The problem analyzes the advantages and disadvantages of the proposed algorithm.Thirdly,a globally fast convergence ant-bird optimization algorithm for task scheduling optimization is proposed.Aiming at the optimization problem of robot group passenger service scheduling in a public environment,the advantages of the good global convergence of the initial solution of the ant colony algorithm and the fast convergence speed of the Sparrow Search Algorithm(SSA)are combined,namely Ant-sparrow optimization algorithm.The algorithm is based on the constraint of the same number of ant colonies and sparrow colonies.The ant colony algorithm transfers to the sparrow search algorithm after a limited number of initial iterations.Aiming at the problem of insufficient bird population diversity at the later stage of its iteration,a divide-and-conquer strategy and probability matrix are introduced to solve the outstanding combination blocks in the feasible solution sequence to ensure the global optimization and rapid convergence of the solution.Finally,a simulation experiment of the optimization algorithm for the autonomous dispatching efficiency of the terminal is designed.Taking a domestic airport terminal as an example,a simulation experiment environment was built;combined with the robot swarm scheduling model and five intelligent optimization algorithms,experiments were designed to verify the convergence of the ant-sparrow optimization algorithm,and the final generation value and passenger waiting time were given.And the waiting probability and the energy consumption required to complete the task.Experiments show that the ant-sparrow optimization algorithm has the characteristics of global optimization and fast convergence speed.It is applied to the optimization problem of robot group passenger service scheduling in public environments such as terminal buildings,and has good practicability.