Aggregation techniques for frequency assignment in public transportation

In public transportation, frequency assignment is a sub-problem of line planning which is responsible for assigning each route of a line a certain frequency with which they are serviced by vehicles. Frequency assignment is among the most important decision problems for optimizing the waiting times in a transportation network and is often a very complex matter. This paper focuses on different aggregation techniques for reducing the computational effort to obtain (near-)optimal line frequencies. In detail, the influence of different model formulations and strategies for customer input data aggregation are investigated. For this purpose, six models are provided, their computational complexity is investigated and suitable mixed-integer mathematical programs are developed. These models vary in the levels of line utilization detail and predict the resulting travel times. Both aggregation techniques are evaluated according to their influence on the solution quality, which is determined by the transport suppliers' point of view as forecast accuracy of the weighted number of customers using the transport. This comprehensive computational study reveals that some model formulations reduce the computational effort considerably by only small losses in line frequency quality. Furthermore, dramatically compressed customer data lead to (near-)optimal line frequencies.