.png){kind=icon}
返回
Dynamic optimization of batch emulsion polymerization using MSIMPSA, a simulated-annealing-based algorithm
.png){kind=icon}
PRE
AI
DOI：10.1021/ie0496784.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The aim of this paper is to present an approach to dynamic off-line optimization of batch emulsion polymerization reactors using a stochastic optimizer. The control objective is to find the optimal temperature profile that minimizes the final batch time constrained by the final conversion and molecular weight. In this study, we evaluate the applicability of MSIMPSA, a simulated-annealing-based algorithm, to solve the optimal control problem. Two cases are studied: first, a simple case without energy balances and, second, a more realistic case using energy balances and constraints on heat transfer. In addition, an SQP optimizer was applied to perform a local optimization around the best results obtained by MSIMPSA. The following conclusions can be drawn from the results: M MSIMPSA can be applied in an easy and straightforward manner (black-box approach) to such optimal control problems. (ii) Even though MSIMPSA is a stochastic algorithm, the best obtained solution is so good that it cannot be further improved by local optimization methods.
Keyword:
GLOBAL OPTIMIZATION
OPTIMAL OPERATION
SEMIBATCH
REACTORS
POLICIES
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
3.9
论文数:
4.0W
被引数:
9.6W
机构
暂无机构信息
引用论文
Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems求解混合整数非线性规划问题的进化算法方法
.png){kind=icon}
PREAI
分享收藏
ANNSA: a hybrid artificial neural network/simulated annealing algorithm for optimal control problems
PREAI
分享收藏
查看更多内容