Aircraft sequencing problem solve by using simulated annealing method
Since commercial aircraft exists in the late 1960’s and early 1970’s, air traffic has experience a tremendous amount of growth and is now known as one of the complex logistical system. Over the past few decades, aircraft sequencing problem (ASP) has become one of the most important area of research...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/81565/1/MuhammadFahmiMohdMFS2017.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Since commercial aircraft exists in the late 1960’s and early 1970’s, air traffic has experience a tremendous amount of growth and is now known as one of the complex logistical system. Over the past few decades, aircraft sequencing problem (ASP) has become one of the most important area of research in the OR field as the number of passengers using the air transportation has increased significantly. ASP aims is to assign each aircraft with scheduled landing time while maintaining the operational and safety constraints. In Malaysia, there is a system called Air Traffic Management (AMAN) that can produce a sequence for the aircraft to land. However, one of the weaknesses of the system is the inability of the system to provide the best route for the aircraft to land even if there is no other aircraft flying at the same period. To tackle this problem, this research will develop a program that can provide the best route for the aircraft to land by considering alternative admissible routes provided by the ATC-KL with the objective of minimizing the total airborne time of all aircrafts while satisfying the separation time constraint between the aircraft. This research will use the Simulated Annealing method with three different neighborhood structures, initial temperatures and temperature reduction formulas. From the computational results, this research has concluded that the best neighborhood structure is Swap and Reroute with an initial temperature of 300 000 and temperature reduction of where P is the random number generated by the program. |
|---|