Abstract
Urban Transit Scheduling Problem (UTSP) is concerned with determining reliable transit schedules for buses and drivers by considering the preferences of both passengers and operators based on the demand and the set of transit routes. This paper considered a UTSP which consisted of frequency setting, timetabling, and simultaneous bus and driver scheduling. A mixed integer multiobjective model was constructed to optimize the frequency of the routes by minimizing the number of buses, passenger’s waiting times and overcrowding. The model was further extended by incorporating timeslots in determining the frequencies during peak and off-peak hours throughout the time period. The timetabling problem studied two different scenarios which reflected the preferences of passengers and operators to assign the bus departure times at the first and last stop of a route. A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. Computational experiments were conducted on the well-known Mandl’s and Mumford’s benchmark networks to assess the effectiveness of the proposed algorithm. Competitive results are reported based on the performance metrics, as compared to other algorithms from the literature.
Highlights
Urban public transportation is an alternative mode for travelers in major cities to commute between destinations
The effectiveness of the proposed parallel MTS (PMTS) algorithm is assessed on benchmark Mandl’s Swiss network (Figure 3) and Mumford’s large network (Figure 4) based on the parameters given in Table 1 using the following performance metrics as suggested by [30]: total number of buses, total waiting times, average route headways, and maximum route headways
A procedure for solving Urban Transit Scheduling Problem (UTSP) which consists of frequency optimization, timetabling, and bus and driver scheduling is proposed
Summary
Urban public transportation is an alternative mode for travelers in major cities to commute between destinations. The study on constructing effective schedules for urban public transportation can be formulated as an optimization problem which is known as the Urban Transit Scheduling Problem (UTSP). UTSP can be divided into a few sub-problems that consist of frequency setting, timetabling, vehicle scheduling and crew scheduling since it is usually difficult to solve them simultaneously due to its numerous objectives and decision variables [1]. The determination of headways or frequency serves as tactical planning to satisfy the irregular demand that changes according to time, days and seasons. This process is important to maintain the quality of transit service, because the unexpected arrival and departure times can affect the service reliability and cause congestion in the transit.
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