A vertical transfer algorithm for the School Bus Routing Problem

Díaz-Parra, Ocotlán; Ruiz-Vanoye, Jorge A.; Buenabad-Arias, Angeles; Cocon, Felipe

doi:10.1109/nabic.2012.6402241

Cited by 14 publications

(10 citation statements)

References 24 publications

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“…The bus route network in Yogyakarta plays an important role in the development of public transportation due to its ability to provide good urban mobility for people rather instead of using a private vehicle (Ceder and Jiang, 2020) to long distances such as office, school, or tourist areas (Pemberton, 2020). The route network generally aims to minimize trip and travel time in order to reduce traffic (Caceres et al, 2017;Diaz-Parra et al, Nov 2012), and public transportation service is required to be developed with equity concept to reach not only the central city but also the suburban area with high demand (Pemberton, 2020). The bus route network plan was, however, determined based on the SK Dirjen 687/2002 as follows (the Republic of Indonesia, 2002).…”

Section: Route Network Planmentioning

confidence: 99%

Route and Bus Stop Plan of Agglomeration Transportation on Educational Facility in Yogyakarta Urban Agglomeration Area

Khaerunnisa

Malkhamah

Suparma

2020

Journal of the Civil Engineering Forum

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Urban Public Transportation has important existence to make good urban transportation. To realize it, the objective of this research is to improve Trans Jogja service as Yogyakarta Urban Agglomeration Transportation that appropriate for student needs. The plan that will be formulated in this research is focused on route and bus stop distribution in educational facility that covering high schools and universities located in Yogyakarta Agglomeration Area. Route plan formulation is done with manual assignment method through total road network trip assignment based on origin destination matrix of school trip. Then, to formulate bus stop plan is done with spatial analytical method that covering bus stop accessibility to schools and universities through 2 scenarios, the first scenario is about 200-meters radius of accessibility and second scenario is 500-meters radius of accessibility. The result is there will be 31 new routes of Yogyakarta Urban Agglomeration Transportation that will reach the whole sub-district in Yogyakarta Agglomeration Area include Godean and Ngemplak Sub-District that previously are not served by Trans Jogja. That new routes are consist of 3 outer city routes (OCR), 23 inner city routes (ICR) and 5 connecting routes that connecting sub-urban and urban area. Then, the bus stop is planned along new route plan and focused on residential land use in sub-urban area, high schools, and universities. On the first scenario with radius of 200-meter, there is 99 units of additional bus stop plan, while on the second scenario with radius of 500 meters is 66 units. Thus, second scenario is assumed better than the first scenario because of more schools and universities are served by Trans Jogja.

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Section: Route Network Planmentioning

confidence: 99%

Route and Bus Stop Plan of Agglomeration Transportation on Educational Facility in Yogyakarta Urban Agglomeration Area

Khaerunnisa

Malkhamah

Suparma

2020

Journal of the Civil Engineering Forum

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“…The algorithm need improvement in travel times and reduced costs. Dí az-Parra et al [24] presents a solution to the School Bus Routing Problem by applying bio-inspired algorithm in the vertical transfer of genetic material to offspring. The genetic algorithm uses clusterization population preselection operator, tournament selection, crossover-k operator and an intelligent mutation operator called mutation-S.…”

Section: A School Bus Routing Problem (Sbrp)mentioning

confidence: 99%

Solving School Bus Routing Problem using Genetic Algorithm-based Model

Oluwadare¹,

Oguntuyi²,

Nwaiwu³

2018

IJISA

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School Bus Routing Problem is an optimization problem which falls under the class of the Vehicle Routing Problem. It involves the use of a fleet of vehicles to efficiently and optimally transport students to and from their schools. To solve this problem, optimal school bus routes are found by minimizing the number of buses, the number of routes and the total distance traversed along all routes. Manual routing of school buses have led to creation of many routes, increased number of buses and several buses navigating the same route, thereby incurring more cost. One of such methods used in solving school bus routing problems is meta-heuristic method which has proven better results in terms of optimal solution and reduced time complexity. In this study, Genetic algorithm is utilized to solve the school bus routing problem because of its simplicity and ability to generate many possible solutions. The algorithm is implemented in C# programming language and tested using secondary data obtained from Ondo State Free-School Bus Shuttle Scheme, Akure, Nigeria. The result shows that of all four nodes (bus stops) used in performance evaluation, Alakure to Oke-Aro junction bus stop presents as the best route which covers a total of 69 nodes with a total distance of 34.5km. This shows that there can be less number of buses in use and reduced number of routes in which the buses are assigned.

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“…The most common objectives of SBRP are minimizing total travel distance or time (8,9,(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22), minimizing total trips (6,7,23,24), and minimizing total cost, including bus purchase (fixed) cost and bus operation cost (3,13,14,(25)(26)(27)(28)(29)(30). The total cost is a combination of the first two objectives because bus purchase cost is proportional to the number of trips (without scheduling, each trip is assumed to be served by one bus), and bus operation cost is equivalent to the total travel distance.…”

Section: Objectivementioning

confidence: 99%

Solving the School Bus Routing Problem by Maximizing Trip Compatibility

Shafahi

Wang

Haghani

2017

Transportation Research Record

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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 homogeneous fleet routing problem that maximizes trip compatibility while minimizing total travel time. This incorporates the trip compatibility for the scheduling problem in the routing problem. Since the problem is inherently just a routing problem, finding a good solution is not cumbersome. To compare the performance of the model with traditional routing problems, we generate eight mid-size data sets. Through importing the generated trips of the routing problems into the bus scheduling (blocking) problem, it is shown that the proposed model uses up to 13% fewer buses than the common traditional routing models.

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A vertical transfer algorithm for the School Bus Routing Problem

Cited by 14 publications

References 24 publications

Route and Bus Stop Plan of Agglomeration Transportation on Educational Facility in Yogyakarta Urban Agglomeration Area

Route and Bus Stop Plan of Agglomeration Transportation on Educational Facility in Yogyakarta Urban Agglomeration Area

Solving School Bus Routing Problem using Genetic Algorithm-based Model

Solving the School Bus Routing Problem by Maximizing Trip Compatibility

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