| dc.creator |
Manumbu, Denis M. |
|
| dc.creator |
Mujuni, Egbert |
|
| dc.creator |
Kuznetsov, Dmitry |
|
| dc.date |
2016-09-21T12:38:38Z |
|
| dc.date |
2016-09-21T12:38:38Z |
|
| dc.date |
2014 |
|
| dc.date.accessioned |
2018-03-27T08:58:10Z |
|
| dc.date.available |
2018-03-27T08:58:10Z |
|
| dc.identifier |
Manumbu, D.M., Mujuni, E. and Kuznetsov, D., Mathematical Formulation Model for a School Bus Routing Problem with Small Instance Data. |
|
| dc.identifier |
2225-0522 |
|
| dc.identifier |
http://hdl.handle.net/20.500.11810/3843 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.11810/3843 |
|
| dc.description |
This paper aims to describe the mathematical formulation model and an exact optimal solution analyses for a
school bus routing problem with small instance data. The formulated model has been used to compute the
optimal solution of time spent by students at all bus stops, apart from that the bus stops are not necessary be
linearly ordered. We also listed down five procedures of mathematical formulation model to reach an exact
optimal solution for a school bus routing problem with small instance data. We assume that each bus has fixed
pick up points, these generates the many possible routes for a bus, the number of routes that generated is equal to
permutation of pick up points, for each route of a bus we computing the objective function and the route with
smallest objective function value can be optimal route of a bus. The sample data from two schools located at Dar
es Salaam are collected and validated in the model to shows the good performing of that model. The optimal
solution results obtained shows that the students spent minimal minutes in new planned routes compared to
current routes. |
|
| dc.language |
en |
|
| dc.subject |
Bus stop |
|
| dc.subject |
Students |
|
| dc.subject |
Buses |
|
| dc.subject |
Optimal value |
|
| dc.subject |
Optimal solution |
|
| dc.subject |
Set |
|
| dc.subject |
Pick up |
|
| dc.title |
Mathematical Formulation Model for a School Bus Routing Problem with Small Instance Data |
|
| dc.type |
Journal Article, Peer Reviewed |
|