Title :
Blending scheduling based on particle swarm optimization algorithm
Author_Institution :
Coll. of Electr. Eng. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China
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;
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
DOI :
10.1109/CCDC.2010.5498157