| dc.contributor |
Business |
|
| dc.contributor |
Business |
|
| dc.creator |
Green, Forrest B. |
|
| dc.date |
2019-01-31T18:07:02Z |
|
| dc.date |
2019-01-31T18:07:02Z |
|
| dc.date |
1982 |
|
| dc.date.accessioned |
2023-03-01T08:10:53Z |
|
| dc.date.available |
2023-03-01T08:10:53Z |
|
| dc.identifier |
http://hdl.handle.net/10919/87183 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/276680 |
|
| dc.description |
A major problem associated with air cargo transport is the assignment and scheduling of aircraft to routes that include several transloading points. This problem is complicated by the fact that shipping quantities vary at each terminal from one day to the next, and there are often wide fluctuations in demand for high priority cargo. Rapid delivery requirements calling for frequent flights to maintain satisfactory service often result in over-assignment and excess capacity. The balancing of capacity and service is a significant problem for air freight carriers.
The problem investigated was to develop a means of evaluating various combinations of aircraft and route schedules taking into account the frequency of flights and the stochastic nature of shipping quantities. Key performance and cost variables were identified, and shipping data were analyzed to determine distribution parameters. A computer simulation model called CARGOSIM was developed to represent the air transport system and provide a tool for the evaluation of various alternatives. The simulation model allows for the stochastic behavior of cargo quantities and the detection of shipment delays due to random surges in demand. Accordingly, both the extent to which assigned aircraft can transport available cargo and the level of service at each terminal are determined through simulation.
The simulation model is used in conjunction with a heuristic designed to search through aircraft types and flight frequency combinations until a least-cost solution is found. The cost function includes both the cost of operating the air transport system and the cost of service delays, thus a balance is achieved between capacity and service when an efficient solution is obtained. This feature represents a decision framework designed so that successive iterations of the simulation model will lead to a least-cost solution within statistically determined margins of error. |
|
| dc.description |
Ph. D. |
|
| dc.format |
viii, 200, [2] leaves |
|
| dc.format |
application/pdf |
|
| dc.format |
application/pdf |
|
| dc.language |
en_US |
|
| dc.publisher |
Virginia Polytechnic Institute and State University |
|
| dc.relation |
OCLC# 9424412 |
|
| dc.rights |
In Copyright |
|
| dc.rights |
http://rightsstatements.org/vocab/InC/1.0/ |
|
| dc.subject |
LD5655.V856 1982.G744 |
|
| dc.subject |
Aeronautics, Commercial -- Freight -- Simulation methods |
|
| dc.title |
Analysis of air cargo transport systems using stochastic simulation |
|
| dc.type |
Dissertation |
|
| dc.type |
Text |
|