2017
DOI: 10.3141/2667-03
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Solving the School Bus Routing Problem by Maximizing Trip Compatibility

Abstract: School bus planning is usually divided into routing and scheduling due to the complexity of solving them concurrently. However, the separation between these two steps may lead to worse solutions with higher overall costs than that from solving them together. When finding the minimal number of trips in the routing problem, neglecting the importance of trip compatibility may increase the number of buses actually needed in the scheduling problem. This paper proposes a new formulation for the multi-school homogene… Show more

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Cited by 21 publications
(14 citation statements)
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References 32 publications
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“…To simplify M-SBRP, they introduced a method that decomposes the original problem into multi-depot and one-school sub-problems. Shafahi et al (2017) focused on improving trip compatibility to increase the number of trips completed by the same bus. Accordingly, a bi-objective function was designed to solve the bus-routing problem with maximum trip compatibility and minimum total travel time.…”
Section: Multiple-school School Bus Routing Problem (M-sbrp) Without mentioning
confidence: 99%
“…To simplify M-SBRP, they introduced a method that decomposes the original problem into multi-depot and one-school sub-problems. Shafahi et al (2017) focused on improving trip compatibility to increase the number of trips completed by the same bus. Accordingly, a bi-objective function was designed to solve the bus-routing problem with maximum trip compatibility and minimum total travel time.…”
Section: Multiple-school School Bus Routing Problem (M-sbrp) Without mentioning
confidence: 99%
“…This formulation is based on the work in Shafahi et al ( 21 ) with some modifications to address the balancing characteristics. It is important to note that since this formulation is based on preprocessing the data, the time window and sub-tour elimination constraints are not needed.…”
Section: Methodsmentioning
confidence: 99%
“…It looks ahead at the valuable scheduling information for routing and makes sure that the interrelationship between routing and scheduling remains intact during the decomposition process. This SCDA algorithm is tested on a set of random problems and problems developed by Shafahi et al 66 SCADA with 0.6% processing time that of integrated models, outperforms traditional decomposition algorithms, and finds a solution with 26% buses and only 7% maximum travel time per trip than Shafahi et al 66 Dewinter et al 19 discusses Police Patrol Routing Problem (PPRP), specifically within the enormous domain of Dynamic Vehicle Routing Problem (DVRP). This review's main objective is the solution, strategies, and algorithms that solve the police patrol routing problem as a dynamic vehicle routing problem.…”
Section: Traffic Police Scheduling Policiesmentioning
confidence: 99%