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ZHAO Xiaoqiang; RONG Gang
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赵小强; 荣冈
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Abstract: Blending is an important unit operation in process industry. 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 satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
Key words: blending scheduling, uncertainty, gasoline blending, particle swarm optimization algorithm, nonlinear optimization
摘要: Blending is an important unit operation in process industry. 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 satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
关键词: 微粒群算法;不确定性;约束优化问题;minmax问题;PSO算法
ZHAO ,Xiaoqiang, RONG ,Gang. Blending Scheduling under Uncertainty Based on Particle Swarm Optimization Algorithm[J]. , DOI: .
赵小强, 荣冈. 基于微粒群优化算法的不确定性调和调度[J]. , DOI: .
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https://cjche.cip.com.cn/EN/Y2005/V13/I4/535