Research On Airport Cargo Optimization Scheduling Based On Improved Bee Colony Algorithm

Aviation logistics industry is an important part of modern transportation structure.With the development of global economy,it is imperative to develop aviation logistics industry and improve the efficiency of cargo turnover in aviation cargo terminal.In view of this problem,this paper explores how to optimize the order of loading and unloading station with the stacker.Firstly,a single elevating transfer vehicle(ETV)scheduling model is established for the airport cargo scheduling problem,and two encoding methods(integer encoding,continuous encoding)are proposed to generate the scheduling sequence to complete the scheduling optimization problem.Aiming at shortening the optimization time,ABC algorithm is parallelized based on multi-core CPU.The experimental results show that the parallelized ABC algorithm with two different encoding methods can effectively complete the freight scheduling task and improve the efficiency and convergence rate.Although the parallel ABC algorithm has achieved better acceleration results,the improvement of quality of solutions is not significant.Since the random single dimension search is performed in ABC algorithm during the process of solutions updating,it may miss the more valuable solutions in other dimensions and the quality of solutions will be affected.In order to further improve the turnover efficiency of airport freight station,with considering the convergence speed,time complexity and accuracy of algorithm,the four improved strategy are proposed.(1)In order to broaden the search range of the solutions,the full-dimensional search ABC algorithm(fdABC)is proposed to update the solutions on each dimension of the solution.(2)To balance the performance of exploration and exploitation,several dimensions are randomly selected to update in the multi-dimensional solution space,that is random multi-dimensional ABC algorithm(RmdABC).(3)Because of the high time complexity of fdABC algorithm,multi-core CPU parallelization processing is introduced whose name is parallel full-dimensional ABC algorithm(PfdABC).(4)In order to improve the accuracy and reduce the time complexity of the algorithm,the better dimensions relative to the current optimal solutions are selected and saved in each iteration to guide the subsequent evolution direction,that is,improved multi-dimensional ABC algorithm(IMABC).The results of benchmark function show that the improved algorithms can effectively solve the problems of time complexity,premature convergence,stagnation and so on.The improved algorithms are applied to the single machine scheduling of airport cargoes.The experimental results show that the improved algorithms can effectively solve the task sets scheduling of airport freight station,and balance the algorithm performance of exploration and exploitation.Finally,on the basic of the single elevating transfer vehicle scheduling model,the twin ETVs scheduling model is established.And the improved artificial colony algorithms are applied to the twin ETVs scheduling,the experimental results show that the IMABC algorithm is superior to other algorithms.It can effectively balance the performance of the exploration and exploitation,and scheduling sequence is reasonable and effective,and the results prove the effectiveness of the improved algorithms.At the same time,compared with single-machine scheduling,the double ETVs scheduling model can be well combined with the actual WMS,greatly improve the scheduling efficiency.