01665nam a2200205 a 4500001001400000003000700014005001700021008004100038020002200079040000800101100002000109245009700129260003400226300005800260502010900318504002500427520096200452650002201414650002301436vtls000077154KUKTEM20251114204558.0140402t2013    my da  f m    000 0 eng d  aTHE0001735(Local)  aUMP1 aTeh, Yung Chuen10aDynamic timetable generator using particle swarm optimization (PSO) method /cTeh Yung Chuen  aKuantan, Pahang :bUMP,c2013  axiii, 42 p. :bill. (some col.) ;c30 cm. +e1 CD-ROM  aProject paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2013  aBibliography : p. 373 aThis 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. 0aLogic programming 0aSwarm intelligence