2009
DOI: 10.1016/j.ejor.2007.10.055
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Solving a school bus scheduling problem with integer programming

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Cited by 88 publications
(48 citation statements)
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“…While the school board could in theory make changes to the bell schedule, they did not do so during the sample period of 1999-2006. The practice of combining school start times and bus scheduling is supported by the Operations Research literature concerning the "school bus problem", where it is well established that cost can be reduced up to 30% if start times and bus routes are simultaneously chosen (Keller and Muller, 1979;Fugenschuh, 2009). …”
Section: Data and Institutional Backgroundmentioning
confidence: 99%
“…While the school board could in theory make changes to the bell schedule, they did not do so during the sample period of 1999-2006. The practice of combining school start times and bus scheduling is supported by the Operations Research literature concerning the "school bus problem", where it is well established that cost can be reduced up to 30% if start times and bus routes are simultaneously chosen (Keller and Muller, 1979;Fugenschuh, 2009). …”
Section: Data and Institutional Backgroundmentioning
confidence: 99%
“…Fügenschuh [29] examines a pickup-and-delivery problem where the students can be transported by at most two buses. To this end, some locations are considered as transfer points where a passenger can go from one vehicle to another.…”
Section: School Bus Routingmentioning
confidence: 99%
“…Fügenschuh [29] presents an integer programming model pursuing the integrated coordination of the school starting times and the public bus services. This approach considered preprocessing techniques, model reformulations, and cutting planes that could be incorporated into a Branch-and-Cut algorithm.…”
Section: School Bus Routingmentioning
confidence: 99%
“…Among alternative modes of transportation, electric public buses become the new trends for urban transportation. There are several studies focused on bus operation, fleet assignment and optimization [1][2][3][4]. Classical approaches for optimization of vehicle scheduling problems seemed inappropriate.…”
Section: Introductionmentioning
confidence: 99%