Study on the random walk classification algorithm of polyant colony

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-01-01 DOI:10.1515/comp-2022-0248

Wenhai Qiu

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Abstract

Abstract With the sustained and healthy development of economy, saving energy and reducing consumption and improving energy utilization rate is a major task that enterprises need to solve. With the complex and large-scale chemical process, the heat exchange network has become complex and diverse. For more and more complex and large-scale industrial heat exchange networks, there are many different kinds of heat exchangers, the flow is complex, so the heat exchange network presents a high degree of complexity, a node status change; its disturbance transfer will influence the stability of other nodes associated with it, because of the system coupling, thus affecting the controllability and reliability of the whole heat exchanger network. Process optimization design of heat exchange network is one of the main methods of energy saving in the industrial field. As a typical simulated evolutionary algorithm in swarm intelligence algorithm, ant colony algorithm combined with random walk classification algorithm, this article proposes an optimized heat transfer network based on multi-ant colony random walk classification algorithm. The heat exchanger was abstracted as a node, and the heat exchanger pipeline was abstracted as a side. According to the maximum geometric multiplicity of the eigenvalue of the adjacency matrix and the linear correlation row vector of the matrix, and combining the importance of the edge of the heat exchange network with the controllable range of the driving edge, the optimal control driving edge of the heat exchange network is identified. The results show that compared with the traditional heat exchanger, the size of the enhanced heat transfer equipment and the influence of pressure drop change. Compared with the results of the size of the heat exchanger strengthening heat transfer equipment and the stepwise optimization of the heat exchange network in this study, the cost of public engineering is reduced by 5.98% and the total cost is reduced by 8.83%.

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多蚁群随机行走分类算法研究

摘要随着经济的持续健康发展，节能降耗、提高能源利用率是企业需要解决的一项重大任务。随着复杂大规模的化学过程，换热网络变得复杂多样。对于越来越复杂、规模越来越大的工业换热网络，换热器种类繁多，流动复杂，因此换热网络呈现出高度复杂、节点状态变化的特点；由于系统的耦合，其扰动传递会影响与其相关的其他节点的稳定性，从而影响整个换热器网络的可控性和可靠性。换热网络的工艺优化设计是工业领域节能的主要方法之一。作为群体智能算法中一种典型的模拟进化算法——蚁群算法与随机游动分类算法相结合，本文提出了一种基于多蚁群随机游动分类法的优化传热网络。将换热器抽象为一个节点，将换热管道抽象为一条边。根据邻接矩阵特征值的最大几何多重性和矩阵的线性相关行向量，结合换热网络边缘的重要性和驱动边缘的可控范围，识别换热网络的最优控制驱动边缘。结果表明，与传统换热器相比，强化传热设备的尺寸和压降的影响都发生了变化。与本研究换热器强化传热设备的尺寸和换热网络的逐步优化结果相比，公共工程成本降低了5.98%，总成本降低了8.83%。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.