Dynamic timetable generator using particle swarm optimization (PSO) method
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...
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2013
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my.ump.umpir.72412023-09-07T01:49:03Z http://umpir.ump.edu.my/id/eprint/7241/ Dynamic timetable generator using particle swarm optimization (PSO) method Chuen, Teh Yung QA Mathematics 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. 2013 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/7241/1/Dynamic%20timetable%20generator%20using%20particle%20swarm%20optimization%20%28PSO%29%20method.pdf Chuen, Teh Yung (2013) Dynamic timetable generator using particle swarm optimization (PSO) method. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. |
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Universiti Malaysia Pahang Al-Sultan Abdullah |
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QA Mathematics |
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QA Mathematics Chuen, Teh Yung Dynamic timetable generator using particle swarm optimization (PSO) method |
| description |
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. |
| format |
Undergraduates Project Papers |
| author |
Chuen, Teh Yung |
| author_facet |
Chuen, Teh Yung |
| author_sort |
Chuen, Teh Yung |
| title |
Dynamic timetable generator using particle swarm optimization (PSO) method |
| title_short |
Dynamic timetable generator using particle swarm optimization (PSO) method |
| title_full |
Dynamic timetable generator using particle swarm optimization (PSO) method |
| title_fullStr |
Dynamic timetable generator using particle swarm optimization (PSO) method |
| title_full_unstemmed |
Dynamic timetable generator using particle swarm optimization (PSO) method |
| title_sort |
dynamic timetable generator using particle swarm optimization (pso) method |
| publishDate |
2013 |
| url |
http://umpir.ump.edu.my/id/eprint/7241/1/Dynamic%20timetable%20generator%20using%20particle%20swarm%20optimization%20%28PSO%29%20method.pdf http://umpir.ump.edu.my/id/eprint/7241/ |
| _version_ |
1822916518104530944 |
| score |
13.251813 |