A Dynamic Planning Model For Check-in Counters Allocation Considering The Activities-Based Cost Method And Multi-Objective Optimization

With the continuous development of China’s economy and society,the group of passengers who choose to travel by air is growing rapidly,there are often situations such as crowded terminals and reduced passenger experience,thus bringing negative impact on civil aviation enterprises.A solution that can realize dynamic planning of check-in counters according to the passenger gathering situation in order to achieve the goal of optimizing passenger queuing time and check-in counter operation cost simultaneously under certain conditions is needed.Based on the previous study,the dynamic allocation model of check-in counters with passenger queuing waiting time and check-in counter operation cost as the optimization objectives is further considered based on the queuing theory and multi-objective optimization theory,and the check-in counter operation cost accounting model is also constructed based on the operation cost method.This research has achieved innovation and breakthrough in the research method of the optimization problem of duty counter allocation,and at the same time revealed the relevant scientific laws based on the optimization results,which provides the theoretical basis for the subsequent scientific researches.The Pareto optimal solution set is obtained by applying NSGA-II algorithm with reference to the relevant materials and data of the case,and then through TOPSIS posterior analysis,the check-in counter allocation scheme with the best comprehensive efficiency is finally obtained for the peak departure time = 05:30-06:00 on the case date,and the check-in counter allocation scheme for the full time T = 04:30-22:30 is obtained simultaneously,compared with the original scheme.The optimized solution for peak hours and full hours achieves optimization in both optimization objectives,and reduces check-in counter operation cost by 3.1% and 14.84%,and reduces the average passenger queuing time by 30.7% and 29.73%,respectively.The results demonstrate that the optimization direction of the two objectives in the Pareto optimal solution set is opposite,and the lower the TOPSIS ranking of the corresponding assignment scheme,the larger the sum of the absolute values of the differences of the optimization objectives.In other periods,the optimized solution has a similar average passenger queuing time as the original plan.Based on the above findings,management recommendations are proposed.