PDF全文下载：2011010080
李学文， 金思毅*， 陶少辉
(青岛科技大学 化工学院，山东 青岛 266042)
摘要： 将一种模拟退火粒子群算法应用于化工过程综合。由于粒子群算法后期进化速度变慢，并易陷入局部极值点，本研究将模拟退火思想应用到粒子群算法中，通过Metropolis准则提高粒子跳出局部极值的能力，并在降温过程中加快了算法后期的进化速度。模拟退火粒子群算法在换热器设计实例和反应器网络综合问题中的应用结果表明，该算法的性能较粒子群算法有了较大改善，同时也表明该算法用于求解化工过程综合问题是可行和有效的。
关键词： 模拟退火粒子群算法； 粒子群算法； 化工过程综合； 反应器网络综合
中图分类号： TP 274 文献标志码: A
Application of Simulated Annealing Particle Swarm Algorithm in Chemical Process Synthesis
LI Xue-wen, JIN Si-yi， TAO Shao-hui
(College of Chemical Engineering, Qingdao University of Science and Technology,Qingdao 266042,China)
Abstract: A hybrid particle swarm optimizaiton algorithm (PSO) based on Simulated Annealing (SA) is introduced for solving chemical process synthesis problems. Because the PSO algorithm has a slow convergence speed and is easy to drop into a local minimum, the SA is integrated into the PSO to effectively avoid the local minimum by Metropolis rule and improve evolutionary rate during temperature decreasing procedures. The simulated annealing particle swarm algorithm is applied to a heat exchanger design example and a reactor network synthesis problem. The calculation results have shown that the performance of the hybrid algorithm is better than that of the particle swarm optimization,and the hybrid algorithm is effective and feasible for solving chemical process synthesis problems.
Key words: simulated annealing particle swarm algorithm；particle swarm algorithm；chemical process synthesis；reactor network synthesis
收稿日期: 2010-09-21
作者简介: 李学文(1985—)，男，硕士研究生. *通信联系人.
