DocumentCode :
2450107
Title :
Multi constrained Route Optimization for Electric Vehicles using SimE
Author :
Siddiqi, Umair F. ; Shiraishi, Yoichi ; Sait, Sadiq M.
Author_Institution :
Dept. of Production Sci. & Technol., Gunma Univ., Ohta, Japan
fYear :
2011
fDate :
14-16 Oct. 2011
Firstpage :
376
Lastpage :
383
Abstract :
Route Optimization (RO) is an important feature of Electric Vehicles (EVs) navigation system. This work performs the RO for EVs using the Multi Constrained Optimal Path (MCOP) problem. The proposed MCOP problem aims to minimize the length of the path and meets constraints on travelling time, time delay due to traffic signals, recharging time and recharging cost. The optimization is performed through a design of Simulated Evolution (SimE) which has innovative goodness, allocation and mutation operations for the route optimization problem. The simulations show that the proposed algorithm has performance almost equal to or better than the Genetic Algorithm (GA) and it requires 0.5N (N is the population size and N ≥ 2 and generally N = 20) times lesser memory than the GA.
Keywords :
delays; electric vehicles; genetic algorithms; navigation; traffic engineering computing; MCOP problem; SimE; electric vehicles; genetic algorithm; multiconstrained optimal path; multiconstrained route optimization; navigation system; simulated evolution; time delay; traffic signals; travelling time; Batteries; Electric vehicles; Equations; Genetic algorithms; Optimization; Roads; Multi Constrained Optimal Path; Route Optimization; Simulated Evolution (SimE);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-1195-4
Type :
conf
DOI :
10.1109/SoCPaR.2011.6089273
Filename :
6089273
Link To Document :
بازگشت