• DocumentCode
    2836605
  • Title

    Blending scheduling based on particle swarm optimization algorithm

  • Author

    Zhao, Xiaoqiang

  • Author_Institution
    Coll. of Electr. Eng. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    1192
  • Lastpage
    1196
  • 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 based on an example of gasoline blending agree satisfactorily with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
  • Keywords
    blending; particle swarm optimisation; blending scheduling; continuous variables; discrete variables; gasoline blending scheduling; general optimization methods; nonlinear optimization problem; particle swarm optimization algorithm; process industry; Constraint optimization; Educational institutions; Electrical engineering; Job shop scheduling; Optimization methods; Particle swarm optimization; Petroleum; Robust control; Scheduling algorithm; Uncertainty; Gasoline Blending; Nonlinear Optimization; PSO Algorithm; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2010 Chinese
  • Conference_Location
    Xuzhou
  • Print_ISBN
    978-1-4244-5181-4
  • Electronic_ISBN
    978-1-4244-5182-1
  • Type

    conf

  • DOI
    10.1109/CCDC.2010.5498157
  • Filename
    5498157