Dra. Ocotlán Díaz-Parra

SBRPLIB

School Bus Routing Problem Library-SBRPLIB

The School Bus Routing Problem Library-SBRPLIB is a depository of test instances of the School Bus Routing Problem. The depository of instances can be downloaded for others researchers for experimentation.

Please cite this depository: Ocotlán Díaz-Parra, Jorge A. Ruiz-Vanoye, José C. Zavala-Díaz. School Bus Routing Problem Library-SBRPLIB. International Journal of Combinatorial Optimization Problems and Informatics, Vol. 2, No. 1 (2011) pp. 23-26.

The School Bus Routing Problem or SBRP is a significant problem in the management of school bus fleet for the transportation of students, each student must be assigned to a particular bus which must be routed in a efficient manner so as to pick up (or return home) each of these students.


Table 1. SBRP instances
 NS SS
PS
 ML
SEE
F
 VN  VC
 BS
XCO
 YCO SN
 EPT  DPT MRT 
MWT
 0
 x0 Y0  SN0  EPT0  DPT0  MRT0 MWT0
...
...
...
...
...
...
...
...
n  xn  Yn  SNn  EPTn  DPTn  MRTn  MWTn


Where NS: Number of School (single or multiple), SS: Surroundings of Service (urban or rural), PS: Problem scope (morning, afternoon, both), ML: Mixed Load (allowed or no allowed), SEE: special-educations students (considered or not considered), F: Fleet mix (homogeneous fleet or heterogeneous fleet), VN: Vehicle Number, VC: Vehicle Capacity, STWb: School Time Windows Begin,  SWTdue: School Time Windows Due, BS: Bus Stop, XCO: X Coord., YCO: Y Coord., SN: Student Number, MRT: Maximum Riding time, EPT: earliest pick-up time, DPT: Due pick-up time, MWT: Maximum Walking Time or distance.

We generated 24 instance set for the School Bus Routing Problem (Table 2). Where NS: Number of School, SS: Surroundings of Service, PS: Problem scope, F: Fleet mix. The urban means routes inside the city, rural means routes outside the city, morning means 7:00-9:00, afternoon means 13:00-16:00, both means morning and afternoon, homogeneous fleet is the vehicle capacity equal in all the fleet, heterogeneous is the vehicle capacity different in all the fleet.

We plan to continuously extend the library with characteristics similar to the ones already presented. The extension depends on the progress made in the development of (meta) heuristic and exact procedures to the School Bus Routing Problem.


Acknowledgements

The author UAEMOR-PTC-231 would like to thank the support to SEP-PROMEP (Mexico) through grant PROMEP/103.5/10/4453.


This site is under construction. The instances will be downloading.

Table 2. SBRP instances sets.

Instance
set
NS
SS
 PS  F I
 S1  1 Urban
 Morning Homogeneous
 50
 S2  1 Urban
Morning
Heterogeneous
 50
 S3  1  Urban Afternoon
 Homogeneous  50
 S4  1  Urban  Afternoon  Heterogeneous  50
 S5  1  Urban  Both  Homogeneous  50
 S6  1  Urban  Both  Heterogeneous  50
 S7  1  Rural  Morning  Homogeneous  50
 S8  1 Rural
 Morning  Heterogeneous  50
 S9  1  Rural  Afternoon  Homogeneous  50
 S10  1  Rural  Afternoon  Heterogeneous  50
 S11  1  Rural Both
 Homogeneous  50
 S12  1 Rural
 Both  Heterogeneous  50
 M1  2-700  Urban Morning
 Homogeneous  50
 M2 2-700
Urban
Morning
 Heterogeneous 50
 M3  2-700  Urban  Afternoon  Homogeneous  50
 M4  2-700  Urban  Afternoon  Heterogeneous  50
 M5  2-700  Urban  Both  Homogeneous  50
 M6  2-700  Urban  Both  Heterogeneous  50
 M7  2-700 Rural
Morning
 Homogeneous  50
 M8  2-700  Rural  Morning  Heterogeneous  50
 M9  2-700  Rural Afternoon
 Homogeneous  50
 M10  2-700  Rural Afternoon
 Heterogeneous  50
 M11  2-700  Rural Both
 Homogeneous  50
 M12  2-700  Rural  Both  Heterogeneous  50

 UAEM1

 1

Urban

 Morning

 Homogeneous

 1

 UAEM2

 1

 Urban

 Afternoon

 Homogeneous

 1



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A CASE STUDY OF THE SCHOOL BUS ROUTING PROBLEM
Solution to the UAEM1.sbrp


Autonomous University of Morelos State is a public institution of higher education larger, coverage, and more important in the state Mexico’s Morelos, with headquarters in the capital, the city of Cuernavaca. The institution has 27 academic units, 5 centers and 2 research units located in 3 campuses campus installed in various municipalities in the state.

A survey (30 surveys peer faculty or 660 surveys) to the students of the 22 university faculties in order to obtain real information of university transport and analyzing their behavior in order to make a proposal to transport college students benefit from the UAEM. The representative sample taken from the  student population is comprised of 30% of students on campus north (Chamilpa) of the UAEM, the university has a total of 11,504 senior students spread over  three campuses, North Campus, east campus and south campus. The figure 2 contains the bus stations necessary to transport some students of the University.
 

Figure 1. University Transport of UAEM.




Figure 2. Cuernavaca and Bus Stop locations of UAEM.



Table 3. Best Route for UAEM instance.
 Vehicles  Routes
 1 Guacamayas, Polvorin, Panteón, Jardín Borda, Glorieta Tlaltenango, Glorieta Zapata, Universidad Base.
 2 Burgos, Tabachines, Acapatzingo, Alta Tensión, Lomas de Teopanzolco, Lomas de Cortes, Chamilpa, Universidad Base.
 3 CIVAC, Chedraui, IMSS, Glorieta la Luna, Plaza Cuernavaca, Domingo Diez, Paloma de la Paz, Estadio Centenario, Universidad Base.


Acknowledgements


The author UAEMOR-PTC-231 would like to thank the support to SEP-PROMEP (Mexico) through grant PROMEP/103.5/10/4453.


Please cite this paper: Ocotlán Díaz-Parra, Jorge A. Ruiz-Vanoye. Marco E. Bustos-De-la-Rosa, Daniel Vázquez-Marban. A genetic algorithm to solve a real-life of School Bus Routing Problem. Optimization 2011, Caparica, Portugal (2011).




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