A practical tool to optimise transit schedule timing points and slack times: An ant algorithm application

Transit Schedule Design (TSD) in this work is defined as selecting the location of timing points and the slack times associated with them. The selection of these variables affects several cost components such as waiting time cost of boarding passengers, in-vehicle waiting time cost of through passengers and the operational cost of transit vehicles. To make a balance between these cost components, the TSD problem must be treated as an optimization problem where the objective is to select a set of timing points and corresponding slack times such that a generalized cost function is minimized. However, this problem takes a considerable amount of time to solve when there are numerous timing point/slack time options. This paper designs a practical algorithm based on the Ant algorithm optimization technique to find an optimal TSD. To check the performance of the algorithm, it is calibrated using the generated data from micro-simulation modelling of a bus route in Melbourne, Australia. The results demonstrate the ability of the developed algorithm to solve the problem for the modelled bus route in a manageable processing time. When the problem becomes more complex, i.e. more feasible schedule designs, the algorithm examines a lower portion of the feasible designs to reach the solution. The paper presents a range of practical benefits of the algorithm in bus route planning