• 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