改进多目标粒子群优化算法在间歇蒸煮过程中的应用  

Application of improved multi-objective particle swarm optimization algorithm in batch cooking process

作　　者：刁东宇[1] 曹正锋[1] 

机构地区：[1]国电南瑞科技股份有限公司,南京210061

出　　处：《计算机应用》2012年第A02期57-60,共4页journal of Computer Applications

摘　　要：对间歇蒸煮过程进行了分析建模,分别建立了纸浆质量、污染指标和制浆成本三个数学模型,从而构成多目标优化问题。在典型的多目标优化算法NSGA-Ⅱ的基础上,采用粒子群算法的消息传递机制来进行求解,新算法在全局极值的选择上借鉴了分布估计算法的概率抽样思想来产生新的gbest。最后就该算法进行了仿真计算并和实际参数进行了对比,说明实际生产在能耗和污染两项指标上确实存在改进的余地。For batch cooking process were analyzed the modeled respectively, the models of pulp quality, pollution index and pulping cost were established, which constitute a multi-objective optimization problem. On the basis of typical multi- objective optimization algorithm named NSGA- II, using the message passing mechanism of the particle swarm algorithm to solve, the new algorithm adopted the probability sampling thought of distribution estimation algorithm to generate new gbest in the ehioce of the global extremum selection. Finally the improved algorithm was simulated and compared to the actual parameters, showing that the actual production in energy consumption and pollution index exist room for improvement.

关 键 词：多目标 粒子群 间歇蒸煮 分布估计算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]