摘要
以C8芳烃混合物的吸附分离过程作为研究对象,应用多目标教学优化算法(multi-objective teachinglearning-based optimization algorithm,MOTLBO)对模拟移动床多目标优化问题进行求解。采用TMB方法,建立了模拟移动床模型,并对两个典型的模拟移动床多目标操作优化问题进行了优化设计。通过与NSGA-Ⅱ算法的比较,证明了多目标教学优化算法在求解模拟移动床多目标优化问题上的有效性和优势。此外,还分析了抽出液流量、抽余液流量以及步进时间等对多目标优化非劣解的影响,优化结果为模拟移动床分离过程的工艺设计和操作提供了依据。
Multi-objective teaching-learning-base optimization （MOTLBO） algorithm has been employed to investigate the multi-objective optimization problem of simulated moving bed chromatography separation for the recovery of p-xylene from a mixture of C8 aromatics. The separation process was simulated using true moving bed （TMB） modeling strategy. Based on the MOTLBO algorithm, the optimal operation conditions are designed for two typical multi-objective optimization problems. Comparing with NSGA-Ⅱ, the MOTLBO algorithm has been verified to be more efficient in solving the multi-objective optimization problem of simulated moving bed. In addition, The influences of the extract flow rate, the raffinate flow rate and the switching time on the pareto optimal solutions were also analyzed. The optimization can facilitate the design and operation of simulated moving bed.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2015年第1期326-332,共7页
CIESC Journal
基金
国家重点基础研究发展计划项目(2012CB720500)
国家自然科学基金项目(U1162202
21206037)
国家高技术研究发展计划项目(2013AA040701)
中国博士后基金项目(2013M531143)
中央高校基本科研业务费专项资金
上海市'科技创新行动计划'研发平台建设项(13DZ2295300)~~
