Title :
A study on intelligent computation of methods of optimization operation for train
Author :
Weidong, Jin ; Chongwei, Li ; Fei, Hu ; Fan, Jin
Author_Institution :
Dept. of Electr. Eng., Southwest Jiaotong Univ., Sichuan, China
Abstract :
Energy-saving train operations are significant both in theory and in applications, but computing the optimization of train operations is very difficult and complex. The optimization computation problem of energy-saving train operations on an undulating-slope line is discussed by means of an intelligent computation model in this paper. To generate the optimal train operation diagram, an intelligent computation model combining local optimization with global optimization is proposed. The local optimization´s numerical functions are obtained from the simulation computation, and the construction of those data is realized by a neural network. The global optimization computation, using a genetic algorithm, generates the train operation diagram. Theoretical analysis and simulation experiments show that the result is satisfactory. Moreover, compared to other methods, not only is the energy saving greater but the computational efficiency is greatly improved too
Keywords :
diagrams; energy conservation; engineering computing; genetic algorithms; neural nets; railways; computational efficiency; energy-saving train operations; genetic algorithm; global optimization; intelligent computation model; local optimization; neural network; numerical functions; optimal train operation diagram; simulation; undulating-slope railway line; Computational modeling; Computer applications; Computer networks; Educational institutions; Energy consumption; Genetic algorithms; Intelligent networks; Kinetic energy; Neural networks; Optimization methods;
Conference_Titel :
Autonomous Decentralized Systems, 2000. Proceedings. 2000 International Workshop on
Conference_Location :
Chengdu
Print_ISBN :
0-7803-6575-5
DOI :
10.1109/IWADS.2000.880893