School bus routing and scheduling with stochastic time-dependent travel times considering on-time arrival reliability

Babaei, Mohsen; Rajabi-Bahaabadi, Mojtaba

doi:10.1016/j.cie.2019.106125

Cited by 20 publications

(14 citation statements)

References 63 publications

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“…It is also suggested that future work should address uncertainty in the bus travel times as this will make the heuristic algorithm more applicable in real-world settings (e.g. [3,7,25]). is as follows:…”

Section: Conclusion and Future Developmentsmentioning

confidence: 99%

A Heuristic Algorithm for School Bus Routing with Bus Stop Selection

Sciortino

Lewis

Thompson

2021

Evolutionary Computation in Combinatorial Optimization

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In this paper a heuristic algorithm is proposed for a school bus routing problem which is formulated as a capacitated and timeconstrained open vehicle routing problem with a homogeneous fleet and single loads. The algorithm determines the selection of bus stops from a set of potential stops, the assignment of students to the selected bus stops, and the routes along the selected bus stops. Its goals are to minimize the number of buses used, the total route journey time and the student walking distances. It also aims at balancing route journey times between buses. The performance of the algorithm is evaluated on a set of twenty real-world problem instances and compared against solutions achieved by a mixed integer programming model. Reported results indicate that the heuristic algorithm finds high-quality solutions in very short amounts of computational time.

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Section: Conclusion and Future Developmentsmentioning

confidence: 99%

A Heuristic Algorithm for School Bus Routing with Bus Stop Selection

Sciortino

Lewis

Thompson

2021

Evolutionary Computation in Combinatorial Optimization

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“…e first type of research on time-dependent travel time directly assumes that travel time is a function related to the time in a day. e travel time function can be piecewise linear form (Sun et al [10]) or distribute function form (Hu et al [11] and Babaei and Rajabi-Bahaabadi [12]). Sun et al [10] applied a travel time function that is piecewise linear and continuous based on the change of speed.…”

Section: Research On Tdvrptwmentioning

confidence: 99%

“…As for the distribution function of travel time, Hu et al [11] built a travel time distribution function and considered the uncertainty of travel time by adding uncertainty budget into the function. Babaei and Rajabi-Bahaabadi [12] assumed that travel time for each time of day satisfies a distribution function and the travel time between specific customers can be calculated by the departure time. e travel time can also be acquired from intelligent transportation system.…”

Section: Research On Tdvrptwmentioning

confidence: 99%

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Spatiotemporal-Dependent Vehicle Routing Problem Considering Carbon Emissions

Liu

Chen

et al. 2021

Discrete Dynamics in Nature and Society

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Aiming to improve the timeliness of logistics distribution and render the optimized route scheme effective under the real traffic network, we study the green vehicle routing problem with dynamic travel speed from both dimensions of time and space. A discrete formulation is proposed to calculate the travel time based on periods and arcs, which allows a vehicle to travel across an arc in multiple periods. Then, we establish a mixed-integer nonlinear programming model with minimum distribution costs including transportation costs, carbon emissions costs, and penalty costs on earliness and tardiness. A hybrid adaptive genetic algorithm with elite neighborhood search is developed to solve the problem. In the algorithm, a neighborhood search operator is employed to optimize elite individuals so that the algorithm can stimulate the intensification and avoid falling into a local optimum. Experimental instances are constructed based on benchmark instances of vehicle routing problem. The numerical results indicate that the proposed algorithm is rather effective in global convergence. Compared with the routing schemes in which travel speed merely varies with time periods or locations, the vehicle route optimized on spatiotemporal-varying speed outperforms them in terms of carbon emissions and timeliness. The research can provide a scientific and reasonable method for logistics enterprises to plan the vehicle schedule focusing on spatiotemporal-dependent speed of the road network.

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“…Liang et al [18] developed a stochastic linear programming model for bus line frequency and passenger path flow under demand and bus travel time uncertainty; its case study shows that this method could significantly benefit public transportation systems. In the joint optimization of school bus routing and scheduling, Babaei et al [19] considered stochastic time-dependent travel times to guarantee that buses arrived on-time at a school with a required reliability level, and proved that the time-dependent character of travel times has a remarkable influence. He et al [20] formulated the dynamic vehicle scheduling problem to tackle trip time stochasticity.…”

Section: Literature Reviewmentioning

confidence: 99%

Reforming mixed operation schedule for electric buses and traditional fuel buses by an optimal framework

Duan

Guan

et al. 2021

IET Intelligent Trans Sys

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Bus scheduling plays a significant role in public transportation and supports the sustainable development of transportation systems. Challenges are beginning to appear with the newly emerging electric buses (EBs), as scheduling changes due to fleet composition make traditional fixed timetables no longer able to satisfy operational needs. Moreover, the fixed-trip time hypothesis has been inappropriate for large cities due to the variety of urban traffic statuses. This paper proposes an optimal framework for reforming the mixed operation schedule for electric buses and traditional fuel buses under stochastic trip times. Based on the primary grouping genetic algorithm (GGA), a straightforward framework with a Monte Carlo simulation is presented to optimize the scheduling scheme. Case studies based on the operating environment and service trips of real bus lines in Beijing are conducted to verify the effectiveness of the proposed model by considering both the composition of fleet types and time stochasticity. Additionally, the impacts of stochasticity, fleet composition, government subsidies and cost factors on operational costs are investigated. Considering stochastic trip times, the achieved scheduling strategies can provide the optimal proportion of electric and traditional fuel buses and make a crucial impact on operational costs. INTRODUCTIONRecently, considering climate change and health impacts, air quality has attracted more attention worldwide [1]. Therefore, reducing the use of fossil fuel is a commonly consentaneous measure [2,3]. In public transportation, most conventional bus types (such as heavy fuel diesel buses) make significant contributions to air pollution and greenhouse gases due to high daily mileages [4,5]. The introduction of electrified transportation solutions is part of a wide range of policy options worldwide [6,7]. Compared with traditional fuel buses (CBs), electric buses (EBs) have considerable inherent advantages such as zero exhaust pipe emissions, lower energy costs, high comfortability, and low noise emissions [8,9]. Therefore, the transformation of the public transport fleet from conventional fuel buses to electric or alternative energy buses can significantly reduce exhaust pipe emissions and improve air quality. At present, EBs have been introduced into the market and operated in many countries (e.g. China, Norway, Sweden, and Germany). However, high ownership costs and limitations on driving range and charging speed make it hard for EBs to com-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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School bus routing and scheduling with stochastic time-dependent travel times considering on-time arrival reliability

Cited by 20 publications

References 63 publications

A Heuristic Algorithm for School Bus Routing with Bus Stop Selection

A Heuristic Algorithm for School Bus Routing with Bus Stop Selection

Spatiotemporal-Dependent Vehicle Routing Problem Considering Carbon Emissions

Reforming mixed operation schedule for electric buses and traditional fuel buses by an optimal framework

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