Research On Collaborative Optimization Method Of Container Location Planning And Loading And Unloading Equipment In Railway Station

In recent years,container railway and waterway multimodal transport has developed rapidly,and the freight volume of port railway station has also increased,which has put forward higher requirements for the operation scheduling of railway station.The operation scheduling of railway station mainly includes two aspects: yard scheduling and mechanical equipment scheduling.How to reasonably stack the containers and arrange the operation equipment to work together,thereby improving the utilization rate of the yard and reducing the cost of mechanical operation,has become an important part of the operation scheduling of the railway station.Therefore,it is of practical significance and certain theoretical value to study the problem of container location planning in railway station and coordinated scheduling of loading and unloading equipment.In response to the above problems,this thesis has carried out research,and the main research contents are as follows:(1)The collaborative scheduling model for container location planning and loading and unloading equipment in the railway station is constructed.To realize the overall operation optimization of railway yard,various constraints in the actual operation process and the synergy between each link are comprehensively considered,and the mathematical model is constructed to describe the relevant resources and state of the railway yard.A railway station benefit function is proposed,which consists of three parts: container turnover,operation equipment completion time and train turnaround time,and the corresponding weight coefficients are designed and normalized.(2)The railway station container operation scheduling algorithm(RSCOSA)is designed to solve the model..Container operation scheduling is to combine yard and loading and unloading equipment to coordinate scheduling.Only when there is available operation equipment can the yard container location planning be arranged,and the result of container location planning directly affects the selection of loading and unloading equipment.Firstly,according to a series of constraint information,a heuristic algorithm based on the principle of layer-by-layer stacking is designed,and the container stacking position with the minimum expected container turnover is calculated.On this basis,determine the operation equipment for the container task,and arrange the operation of the mechanical equipment.Then the improved genetic algorithm is used to solve the container job scheduling problem.Aiming at the invalid solutions in the population,the gene repair strategy is designed,and the adaptive crossover and mutation probability are designed to improve the global and local search ability and avoid falling into the local optimum.Finally,the effectiveness of the improved algorithm is verified by experiments.(3)Experimental verification.Firstly,a simulation strategy based on the event scheduling method is designed to verify the validity of the model.Then,based on the model,combined with the actual data in the field,the RSCOSA algorithm was compared with the LSHA algorithm(Heuristic algorithm based on the lowest stack),GA algorithm(Genetic Algorithm)and manual scheduling.The experimental results show that although the RSCOSA algorithm is not as good as the LSHA algorithm and the manual scheduling in the turnover rate,considering the overall operation efficiency,the RSCOSA algorithm is superior to the LSHA algorithm,GA algorithm and the manual scheduling algorithm,thus verifying the effectiveness of the RSCOSA algorithm.Finally,analyze the operation area of the yard crane,and verify that the sub-regional operation plan can effectively improve the operation efficiency under the same scale calculation example.In summary,to solve the problem of container operation scheduling in the railway station,this thesis builds the mathematical model and designs a container operation scheduling algorithm.The simulation experiment is designed based on the model,and the experiment shows that the RSCOSA algorithm can better solve the actual production problem of the port compared with the manual scheduling,GA algorithm and LSHA algorithm.