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008 170822s2017 my a f m 000 0 eng d
020 _aTHE0005312(Local)
039 9 _a201905151045
_bhanafiah
_c201712061144
_dhuda
_y201708221432
_zsaini
040 _aUMP
090 _aFKP .A953 2017 r Bc.
100 0 _aAzlan Ahmad Tajuddin
245 1 0 _aSolving gate allocation problem (AGAP) using distance-evaluated particle swarm optimization (DEPSO) /
_cAzlan Ahmad Tajuddin
260 _aKuantan, Pahang :
_bUMP,
_c2017
300 _axii, 79 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
500 _aFaculty of Manufacturing Engineering
502 _aProject Paper (Bachelor of Mechatronics Engineering (Hons.)) -- Universiti Malaysia Pahang – 2017
504 _aBibliography: p. 62-63
520 _aAssignment 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.
610 2 0 _aFaculty of Manufacturing Engineering
_xDissertations
650 0 _aUniversities and Colleges
_xDissertations
650 0 _aTheses
856 4 0 _uhttp://ecollib.ump.edu.my/27199/
_zAccess in library only
999 _aVIRTUA40
_c7533
_d7539
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