01913nam a2200253 a 4500 vtls000077154 KUKTEM 20251114204558.0 140402t2013 my da f m 000 0 eng d THE0001735(Local) 201905131215 yusri 201404030757 Fida 201404021327 Fida UMP QA76.63 .T44 2013 rs Bc. Teh, Yung Chuen Dynamic timetable generator using particle swarm optimization (PSO) method / Teh Yung Chuen Kuantan, Pahang : UMP, 2013 xiii, 42 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2013 Bibliography : p. 37 This paper addresses the usage of Particle Swarm Optimization (PSO) in generating a timetable which the selection of driver and vehicle are based on the concept of PSO. The objectives are simultaneously considered as follow: 1) minimizing the cycle time, 2) regenerate the timetable. Searching for an optimal solution in such of large sized population will be time consuming and thus by presenting the PSO method is able to select the appropriate driver and vehicle with a shorter period. The timetable that is generated will be more appropriate as regenerating function can handle emergency such as breakdown of vehicle. Besides, during the generating of timetable, it also considers constraints which make the task more challenging. The chosen particle during implementing the PSO method should be chosen with fitness nearest to fifty in this system. Thus, the timetable for transport schedule system can be arranged without clashing of driver or vehicle. Logic programming Swarm intelligence 0 0 0 1 20000 20000 2019-09-04 0 QA76.63 .T44 2013 rs Bc. 0000078850 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7604 | QA76.63 .T44 2013 rs Bc. 0000078851 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4447 4453 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992