• DocumentCode
    3264887
  • Title

    Gasoline Blending Scheduling Based on Uncertainty

  • Author

    Zhao, Xiaoqiang ; Wang, Ying

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China
  • Volume
    2
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    84
  • Lastpage
    87
  • Abstract
    Blending is an important unit operation in process industry. Gasoline blending scheduling is nonlinear optimization problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both continuous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results illustrate that the PSO algorithm is valid and effective for the gasoline blending scheduling problem under uncertainty.
  • Keywords
    blending; fuel processing industries; particle swarm optimisation; petroleum; scheduling; gasoline blending scheduling; nonlinear optimization problem; particle swarm optimization algorithm; process industry; Constraint optimization; Educational institutions; Environmental economics; Job shop scheduling; Optimal scheduling; Particle swarm optimization; Petroleum; Processor scheduling; Scheduling algorithm; Uncertainty; PSO algorithm; gasoline blending scheduling; nonlinear optimization; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.206
  • Filename
    5231039