02228ntm a2200289 a 4500 vtls000101050 KUKTEM 20251117113354.0 170822s2017 my a f m 000 0 eng d THE0005312(Local) 201905151045 hanafiah 201712061144 huda 201708221432 saini UMP FKP .A953 2017 r Bc. Azlan Ahmad Tajuddin Solving gate allocation problem (AGAP) using distance-evaluated particle swarm optimization (DEPSO) / Azlan Ahmad Tajuddin Kuantan, Pahang : UMP, 2017 xii, 79 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM 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. Faculty of Manufacturing Engineering Dissertations Universities and Colleges Dissertations Theses http://ecollib.ump.edu.my/27199/ Access in library only 0 0 0 1 20000 20000 2019-09-04 0 FKP .A953 2017 r Bc. 0000119167 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 20000 20000 2019-09-04 0 CD 10800 | FKP .A953 2017 r Bc. 0000119168 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 7533 7539 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5000*5020*5040*5200*6100*6500*6501*8560*9992