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Solving gate allocation problem (AGAP) using distance-evaluated particle swarm optimization (DEPSO) / Azlan Ahmad Tajuddin

By:

Azlan Ahmad Tajuddin

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2017Description: xii, 79 p. : ill. (some col.) ; 30 cm. + 1 CD-ROMISBN:

THE0005312(Local)

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Dissertation note: Project Paper (Bachelor of Mechatronics Engineering (Hons.)) -- Universiti Malaysia Pahang – 2017 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.

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Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	FKP .A953 2017 r Bc. (Browse shelf(Opens below))	1	Not for loan		0000119167
Final Year Report	UMPLIB PEKAN	CD 10800 \| FKP .A953 2017 r Bc. (Browse shelf(Opens below))	1	Not for loan		0000119168

Faculty of Manufacturing Engineering

Project Paper (Bachelor of Mechatronics Engineering (Hons.)) -- Universiti Malaysia Pahang – 2017

Bibliography: p. 62-63

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.