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
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;
Conference_Titel :
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3645-3
DOI :
10.1109/CINC.2009.206