Solving gate allocation problem (AGAP) using distance-evaluated particle swarm optimization (DEPSO)
Assignment of flights to gates at an airport become very complex nowadays, especially for unprepared airport. In this investigation, the airport gate allocation problem is solved using a recently introduced Meta-heuristic and also one of the extensions from Particle Swarm Optimization (PSO) which is...
Saved in:
| Main Author: | |
|---|---|
| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/18697/1/Solving%20gate%20allocation%20problem%20%28AGAP%29%20using%20distance-evaluated%20particle%20swarm%20optimization%20%28DEPSO%29.pdf http://umpir.ump.edu.my/id/eprint/18697/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Assignment of flights to gates at an airport become very complex nowadays, especially for unprepared airport. In this investigation, the airport gate allocation problem is solved using a recently introduced Meta-heuristic and also one of the extensions from Particle Swarm Optimization (PSO) which is called Distance-Evaluated Particle Swarm Optimization (DEPSO). The first objective of this investigation is to minimize the passengers; total walking distance from gate to exit/entrance and from gate to gate (transit). Since the airport gate allocation problem is a discrete combinatorial problem, the original continuous PSO is extended to DEPSO such that PSO can be used to solve these discrete combinatorial problem. After that, the second objectives is to evaluate the performance of the DEPSO manually using Excel. Last but not least, a small real life problem or an application for the case study, an airport with 40 flights, 14 numbers of plane and 16 gates has been successfully optimized using DEPSO algorithm. |
|---|