DocumentCode :
3209538
Title :
The research in public transit scheduling based on the improved genetic simulated annealing algorithm
Author :
Zhu, Chang-Sheng ; Huang, Hong-Yong ; Yuan, Yuan ; Wang, Qing-Rong
Author_Institution :
Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
Volume :
2
fYear :
2010
fDate :
13-14 Sept. 2010
Firstpage :
273
Lastpage :
276
Abstract :
In this work,we set up public transit planning model by analysing of vehicle dispatching and taking both interest of bus company and passenger into consideration. using the improved genetic simulated annealing algorithm(the improved GA-SA) to carry out optimization for public transit dispatching model,and overcomes the problems such as evolution is slow,precocious, local optimal solution and so on, it can find the approximate optimum solution, reliably, from the huge search space of scheduling optimization problem. intelligent scheduling optimization problem in the great search space to find reliable optimal solution or approximate optimal solution. Finally,we use MATLAB to carry on simulation experiment. the results show that the improved GA-SA has higher efficiency than traditional GA.
Keywords :
genetic algorithms; simulated annealing; transportation; MATLAB; bus company; improved genetic simulated annealing algorithm; public transit scheduling; scheduling optimization problem; vehicle dispatching; Algorithm design and analysis; Annealing; Biological system modeling; Gallium; Genetics; Optimization; Transportation; genetic algorithm; genetic-simulated annealing algorithm; intelligent scheduling; public transit; the simulated annealing algorith;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7705-0
Type :
conf
DOI :
10.1109/CINC.2010.5643737
Filename :
5643737
Link To Document :
بازگشت