Multiple tabu search for multiobjective urban transit scheduling problem

The study of urban public transportation is essential for building an efficient transit system that can minimize the traffic congestion, reduce pollutions and increase the mobility of a community. Urban Transit Scheduling Problem (UTSP) considers the process of creating timely transit schedules that includes bus and drivers assignment based on the users’ and operators’ requirements. It is necessary to achieve a tradeoff between the interest of users and operators which lead to multiobjective nature of UTSP. This paper studies multiobjective UTSP consisting of frequency setting, timetabling, simultaneous bus and driver scheduling by applying a Multiple Tabu Search (MTS) algorithm. In addition, a multiobjective set covering model is also adapted by including some real-world restrictions to find adequate number of buses and drivers. The MTS algorithm is tested on benchmark instances from Mandl’s Swiss Network. The computational results shown that the algorithm able to produce comparable results for most cases from the literature.

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