A multi-loading school bus routing problem

Miranda, Douglas Moura; Camargo, Ricardo Saraiva de; Conceição, Samuel Vieira; Porto, Marcelo Franco; Nunes, Nilson Tadeu Ramos

doi:10.1016/j.eswa.2018.02.014

Cited by 39 publications

(35 citation statements)

References 39 publications

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“…Further, the mixed load school bus routing problems with multi-objectives or heterogeneous fleet were studied in [19,20]. Recently, new SBRP research give emphasis to the more complex real world mixed load SBRP problems [21,22], which addresses the contemporary trends of SBRP.…”

Section: Literature Reviewmentioning

confidence: 99%

A Metaheuristic Algorithm for Routing School Buses With Mixed Load

et al. 2020

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Designing a system to solve school bus routing problems (SBRP), especially in a large school district, is very complex and expensive. One of the challenges resides in designing routes for the school buses when they have mixed loads, where each bus transports students for one or more schools at the same time to save the total number of buses required. This article aims to explore whether the algorithm originally developed for pickup and delivery problem with time windows (PDPTW) can be employed for solving mixed load SBRP. We present a PDPTW-based algorithm to address the mixed load SBRP focusing on minimizing the number of buses required. Our algorithm combines a record-to-record travel framework with three neighborhood operators, single paired insertion, swapping pairs between routes, and within route insertion, to improve solution iteratively. Results from implementing this algorithm show that our PDPTW-based algorithm is feasible for mixed load SBRP. Moreover, we found that guided strategy is better than random for permuting nodes that would be selected to relocate positions in a route or among routes. In addition, the results also show that the spatiotemporal connectivity index used in our algorithm can reduce the computation time needed for searching for solutions without affecting the quality of the solutions.

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Section: Literature Reviewmentioning

confidence: 99%

A Metaheuristic Algorithm for Routing School Buses With Mixed Load

et al. 2020

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“…The number of buses used (N) and the total bus travel distance or time (TBD) were mostly adopted to assess the performance, as shown in Table 1 . A few works also employed total student riding or walking distance (TSD), child’s time loss (TL), and transportation cost (TC) as the measures [ 1 , 2 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Due to the increased demand of the school bus system in the real world and the appearance of routing and scheduling issues during the operation of a vehicle fleet, the School Bus Routing Problem (SBRP) has been widely studied. SBRP can be regarded as a combinatorial optimization problem which have specific assumptions and constraints [ 1 ]. It consists of several sub-problems which can be summarized as “bus stop selection problem”, “route generation problem”, “school bell time adjustment problem” and “route scheduling problem” [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the re-arrangement of school time must be permitted in the “school bell adjustment problem”, as well as the scheduling of the bus fleet for multiple schools should be allowed. Regarding the students from different schools, whether a mixed load being allowed to get on the same bus at the same time is also considered as an important assumption in the sub-problem of “bus route scheduling” [ 1 , 8 , 9 , 11 ]. Nevertheless, other than the situation in Korea and other countries in Asia, the school bus fleet in China is mostly operated by the individual school itself.…”

Section: Introductionmentioning

confidence: 99%

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School bus routing problem in the stochastic and time-dependent transportation network

Sun

Duan

2018

PLoS ONE

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Accidents, bad weathers, traffic congestions, etc. led to the uncertainties of travel times in real-life road networks, which greatly affected the quality of individual’s life and the reliability of transportation system. This paper addressed the school bus routing problem in such a stochastic and time-dependent road environment. Firstly, the problem was set based on a single-school configuration, and the students were picked up at their homes, which was in line with the current situation of school bus systems in China. Thus, it could be regarded as an independent problem of school bus route generation in random dynamic networks, which could be solved as a variant of extended Vehicle Routing Problem. However, due to the fluctuation and uncertainty of link travel times, the arrival time at each stop including the destination was varying. Therefore, the selection of optimal path connecting the current service node with the next one was treated as a sub-problem in this study, where the reliability of travel times in the stochastic and time-varying network was highly concerned by such time-rigid commuters. To this end, a Robust Optimal Schedule Times model with a hard time windows constraint was built to generate a most cost-reliable route for school buses. By the use of Robust Optimization method, it was intended to minimize the worst-case total cost which combined the cost of earlier schedule delays with the disutility of travel times. It was also proved that the proposed model could be converted into solving a conventional problem in deterministic dynamic networks for a reduction of computation complexity, which provided the potential of applying to the practical problems. Finally, the validity of the proposed model and its performance evaluation was analyzed through a small-scale computational instance, where all the link travel times in the simulated network were attributed to both time-varying and stochastic. Then, a mathematical programming solver was used to find the exact optimal solution. The results indicated that the model was valid, and the necessity of considering the stochastic and time-dependent nature of transportation networks was also confirmed in the case study.

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“…Souza Lima et al [5,6] deal with a multiobjective capacitated rural school bus routing problem with heterogeneous fleet and mixed loads. Miranda et al [7] expand the concept of mixed-load to multi-load, which means that the students can be picked up and delivered simultaneously. Taking into account that the use of private cars depends on how well public transportation systems operate, Parvasi et al [8] formulate a bilevel mathematical model, which considers the possibility of estimating the number of students who choose the public transport system.…”

Section: Introductionmentioning

confidence: 99%

A Partial Allocation Local Search Matheuristic for Solving the School Bus Routing Problem with Bus Stop Selection

et al. 2020

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This paper addresses the school bus routing problem with bus stop selection, which jointly handles the problems of determining the set of bus stops to visit, allocating each student to one of these bus stops and computing the routes that visit the selected bus stops, so that the total routing cost is minimized and the walking distance of the students is limited by a given value. A fast and efficient matheuristic is developed based on an innovative approach that first partially allocates the students to a set of active stops that they can reach, and computes a set of routes that minimizes the routing cost. Then, a refining process is performed to complete the allocation and to adapt the routes until a feasible solution is obtained. The algorithm is tested on a set of benchmark instances. The computational results show the efficiency of the algorithm in terms of the quality of the solutions yielded and the computing time.

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A multi-loading school bus routing problem

Cited by 39 publications

References 39 publications

A Metaheuristic Algorithm for Routing School Buses With Mixed Load

A Metaheuristic Algorithm for Routing School Buses With Mixed Load

School bus routing problem in the stochastic and time-dependent transportation network

A Partial Allocation Local Search Matheuristic for Solving the School Bus Routing Problem with Bus Stop Selection

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