间歇自由基聚合反应器的Pareto蚁群优化  

Pareto ant colony optimization to batch free-radical polymerization reactors

作　　者：郭相坤[1] 王晓静[2] 许德平[1] 王晓玲[1] 

机构地区：[1]中国矿业大学北京化学与环境工程学院,北京100083 [2]北京建筑工程学院理学院,北京100044

出　　处：《计算机与应用化学》2009年第6期732-736,共5页Computers and Applied Chemistry

摘　　要：优化技术广泛用于化工生产中"最佳"工艺条件的确定,工程师常需在无先验信息情况下,从若干工艺条件中确定同时能满足多方需求的最佳方案,实现效益最大化。枚举法只能在较简单的情况下使用,随着生产实际复杂程度的增加,枚举法显得无能为力。近来提出的元启发式蚁群优化算法无论计算时间,还是优化质量,都能满足复杂体系的优化。本研究采用Pareto蚁群算法,对间歇自由基聚合反应器进行了多目标优化,结果表明,该算法具有较强的鲁棒性,可用于间歇自由基聚合反应器的设计。Optimization technologies are widely used in chemical industry for chemical engineers to select the ＂best＂ manipulating profile out of a given set of technological conditions. The engineers must consider multiple objectives and can improve their opportunities by determining and exploring the solution space of all efficient solutions interaetively with little a priori preference information available. However, the enumerative method only works on small instances arid the underlying complex optimization problems become increasingly demanding as the number of projects grow. The recently developed meta-heuristics, Ant Colony Optimization Algorithms, provide a useful compromise between the computation time and the quality of the approximated solution space. In this study, a Pareto Ant Colony Optimization Algorithm was applied to a real world batch polymerization process of multi-objective optimization. The results indicate that the algorithm is robust and useful for the chemical process optimization.

关 键 词：多目标优化 蚁群算法 间歇自由基聚合反应器 PARETO最优集 

分 类 号：O6[理学—化学] TQ46[化学工程—制药化工]