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Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng WU

《工程管理前沿（英文）》 2020年第7卷第2期页码 169-171 doi: 10.1007/s42524-020-0114-4

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CORRECTION to: Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng Wu

《工程管理前沿（英文）》页码 697-697 doi: 10.1007/s42524-020-0139-8

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A literature review of perishable medical resource management

《工程管理前沿（英文）》页码 710-726 doi: 10.1007/s42524-023-0278-9

摘要： In recent decades, healthcare providers have faced mounting pressure to effectively manage highly perishable and limited medical resources. This article offers a comprehensive review of supply chain management pertaining to such resources, which include transplantable organs and healthcare products. The review encompasses 93 publications from 1990 to 2022, illustrating a discernible upward trajectory in annual publications. The surveyed literature is categorized into three levels: Strategic, tactical, and operational. Key problem attributes and methodologies are analyzed through the assessment of pertinent publications for each problem level. Furthermore, research on service innovation, decision analytics, and supply chain resilience elucidates potential areas for future research.

关键词： perishable medical resources organ transplant healthcare products decision analytics operations management

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Data analytics and optimization for smart industry

Lixin TANG, Ying MENG

《工程管理前沿（英文）》 2021年第8卷第2期页码 157-171 doi: 10.1007/s42524-020-0126-0

摘要： Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries. Motivated by the major development strategies and needs of industrial intellectualization in China, this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization, as well as their application to smart industrial engineering. First, this study describes a general methodology for the fusion of data analytics and optimization. Then, it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing. Finally, it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization. The framework uses data analytics to perceive and analyze industrial production and logistics processes. It also demonstrates the intelligent capability of planning, scheduling, operation optimization, and optimal control. Data analytics and system optimization technologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing, resources and materials, energy, and logistics systems, such as high energy consumption, high costs, low energy efficiency, low resource utilization, and serious environmental pollution. The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency. Therefore, industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.

关键词： data analytics system optimization smart industry

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Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

《工程管理前沿（英文）》 2017年第4卷第1期页码 41-48 doi: 10.15302/J-FEM-2017003

摘要： A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it’s needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.

关键词： engineering management project management big data data analytics planning execution

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Special issue: Operations analytics and optimization for manufacturing, logistics and energy systems

Jiming WANG, Jie LIU, Anlin SHAO, Lixin TANG

《工程管理前沿（英文）》 2017年第4卷第3期页码 239-241 doi: 10.15302/J-FEM-2017109

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Convergence to real-time decision making

James M. TIEN

《工程管理前沿（英文）》 2020年第7卷第2期页码 204-222 doi: 10.1007/s42524-019-0040-5

摘要： Real-time decision making reflects the convergence of several digital technologies, including those concerned with the promulgation of artificial intelligence and other advanced technologies that underpin real-time actions. More specifically, real-time decision making can be depicted in terms of three converging dimensions: Internet of Things, decision making, and real-time. The Internet of Things include tangible goods, intangible services, ServGoods, and connected ServGoods. Decision making includes model-based analytics (since before 1990), information-based Big Data (since 1990), and training-based artificial intelligence (since 2000), and it is bolstered by the evolving real-time technologies of sensing (i.e., capturing streaming data), processing (i.e., applying real-time analytics), reacting (i.e., making decisions in real-time), and learning (i.e., employing deep neural networks). Real-time includes mobile networks, autonomous vehicles, and artificial general intelligence. Central to decision making, especially real-time decision making, is the ServGood concept, which the author introduced in an earlier paper (2012). It is a physical product or good encased by a services layer that renders the good more adaptable and smarter for a specific purpose or use. Addition of another communication sensors layer could further enhance its smartness and adaptiveness. Such connected ServGoods constitute a solid foundation for the advanced products of tomorrow which can further display their growing intelligence through real-time decisions.

关键词： real-time decision making services goods ServGoods Big Data Internet of Things artificial intelligence wireless communications

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Current applications of artificial intelligence for intraoperative decision support in surgery

Allison J. Navarrete-Welton, Daniel A. Hashimoto

《医学前沿（英文）》 2020年第14卷第4期页码 369-381 doi: 10.1007/s11684-020-0784-7

摘要： Research into medical artificial intelligence (AI) has made significant advances in recent years, including surgical applications. This scoping review investigated AI-based decision support systems targeted at the intraoperative phase of surgery and found a wide range of technological approaches applied across several surgical specialties. Within the twenty-one ( =21) included papers, three main categories of motivations were identified for developing such technologies: (1) augmenting the information available to surgeons, (2) accelerating intraoperative pathology, and (3) recommending surgical steps. While many of the proposals hold promise for improving patient outcomes, important methodological shortcomings were observed in most of the reviewed papers that made it difficult to assess the clinical significance of the reported performance statistics. Despite limitations, the current state of this field suggests that a number of opportunities exist for future researchers and clinicians to work on AI for surgical decision support with exciting implications for improving surgical care.

关键词： artificial intelligence decision support clinical decision support systems intraoperative deep learning computer vision machine learning surgery

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Challenges of human–machine collaboration in risky decision-making

《工程管理前沿（英文）》 2022年第9卷第1期页码 89-103 doi: 10.1007/s42524-021-0182-0

摘要： The purpose of this paper is to delineate the research challenges of human–machine collaboration in risky decision-making. Technological advances in machine intelligence have enabled a growing number of applications in human–machine collaborative decision-making. Therefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilities. In risky decision-making, a human decision-maker is vulnerable to cognitive biases when judging the possible outcomes of a risky event, whereas a machine decision-maker cannot handle new and dynamic contexts with incomplete information well. We first summarize features of risky decision-making and possible biases of human decision-makers therein. Then, we argue the necessity and urgency of advancing human–machine collaboration in risky decision-making. Afterward, we review the literature on human–machine collaboration in a general decision context, from the perspectives of human–machine organization, relationship, and collaboration. Lastly, we propose challenges of enhancing human–machine communication and teamwork in risky decision-making, followed by future research avenues.

关键词： human–machine collaboration risky decision-making human–machine team and interaction task allocation human–machine relationship

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Erratum to: Theoretical foundation of a decision network for urban development

Shih-kung Lai, Jhong-you Huang,lai@tongji.edu.cn,jhongyouhuang@gmail.com

《信息与电子工程前沿（英文）》 2017年第18卷第10期页码 1677-1677 doi: 10.1631/FITEE.15e0000

摘要： Erratum to: , 2017 18(8):1033-1039. doi:

关键词： Decision making Linked decisions Decision network Planning

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RCAnalyzer：动态网络中稀有类可视分析系统 Research

Jia-cheng PAN, Dong-ming HAN, Fang-zhou GUO, Da-wei ZHOU, Nan CAO, Jing-rui HE, Ming-liang XU, Wei CHEN

《信息与电子工程前沿（英文）》 2020年第21卷第4期页码 491-506 doi: 10.1631/FITEE.1900310

摘要：动态网络是指其节点和/或链接随时间动态变化的图结构。现有可视化和分析技术主要集中在总结和揭示网络结构的主要演化模式。很少有工作专注于检测动态网络中的异常变化模式，这种情况很少发生，一旦发生，则可能破坏整个结构的发展。本文介绍了第一个可视分析系统RCAnalyzer，用于检测动态网络中子结构的罕见变化。所提系统采用稀有类别检测算法识别异常变化的结构，并在上下文中将其可视化，以帮助专家检查分析结果并标记数据。特别地，引入新的可视化形式，用一系列连接的三角矩阵表达动态网络快照。在每个矩阵上进行层次聚类和最佳树切割，以展示在其周围结构的上下文中检测到的节点和链接的罕见变化。通过案例和用户调研评估该技术。评估结果验证了该系统的有效性。

关键词：稀有类检测；动态网络；可视分析

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An overview on the applications of the hesitant fuzzy sets in group decision-making: Theory, support

Zeshui XU, Shen ZHANG

《工程管理前沿（英文）》 2019年第6卷第2期页码 163-182 doi: 10.1007/s42524-019-0017-4

摘要： Due to the characteristics of hesitant fuzzy sets (HFSs), one hesitant fuzzy element (HFE), which is the basic component of HFSs, can express the evaluation values of multiple decision makers (DMs) on the same alternative under a certain attribute. Thus, the HFS has its unique advantages in group decision making (GDM). Based on which, many scholars have conducted in-depth research on the applications of HFSs in GDM. We have viewed lots of relevant literature and divided the existing studies into three categories: theory, support and methods. In this paper, we elaborate on hesitant fuzzy GDM from these three aspects. The first aspect is mainly about the introduction of HFSs, HFPRs and some hesitant fuzzy aggregation operators. The second aspect describes the consensus process under hesitant fuzzy environment, which is an important support for a complete decision-making process. In the third aspect, we introduce seven hesitant fuzzy GDM approaches, which can be applied in GDM under different decision-making conditions. Finally, we summarize the research status of hesitant fuzzy GDM and put forward some directions of future research.

关键词： hesitant fuzzy set hesitant fuzzy preference relation group decision-making

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Clinical decision-making by the emergency department resident physicians for critically ill patients

null

《医学前沿（英文）》 2012年第6卷第1期页码 89-93 doi: 10.1007/s11684-012-0183-9

摘要：

The application of main methodologies for clinical decision-making by residents in emergency medical practice was assessed, and issues in this area were investigated. The treatments provided to 2 611 critical patients by the Peking Union Medical College Hospital of were analyzed by independent investigators who evaluated the main clinical decision-making processes applied by the hospital residents. The application of decision-making strategies by PG1 and PG3 groups, which means the residents in first year and the third year, were compared. The patients were treated according to pattern recognition (43.0%), hypothetico-deductive reasoning (23.4%), event-driven models (19.3%), and rule-using algorithms (5.9%). A significant difference was found between PG1 and PG3 groups (χ²=498.01, P<0.001). Pattern recognition and hypothetic-deductive methods were the most common techniques applied by emergency physicians in evaluating critically ill patients. The decision-making processes applied by junior and senior residents were significantly different, although neither group adequately applied rule-using algorithms. Inclusion of clinical decision-making in medical curricula is needed to improve decision-making in critical care.

关键词： clinical decision-making emergency medicine critically ill patient resident methodology

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双枝模糊决策与决策识别问题

史开泉,李歧强

《中国工程科学》 2001年第3卷第1期页码 71-77

摘要：

文章提出具有中性域X^*(X^*≠{x})X的上的双枝模糊决策的概念和决策优化分析模型、决策判定定理、决策识别定理、决策去余定理和决策因素域X上的挖洞原理。双枝模糊决策具有下列特征：决策结论的双向依赖特性，决策结论的叠加合成特性，决策结论的枝-分离特性，决策结论的枝-退化特性，决策结论的非失误特性。研究结果得到了应用。

关键词：双枝模糊决策决策模型决策判定定理决策识别定理决策去余定理挖洞原理

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BMP decision support system for evaluating stormwater management alternatives

Mow-Soung CHENG, Jenny X. ZHEN, Leslie SHOEMAKER,

《环境科学与工程前沿（英文）》 2009年第3卷第4期页码 453-463 doi: 10.1007/s11783-009-0153-x

摘要： Prince George’s County, Maryland, in the Washington D.C. metropolitan area has developed a best management practice decision support system (BMPDSS) to support analysis and decision making for stormwater management planning and design at both the site scale and the watershed levels. This paper presents a detailed description of the BMPDSS. A case study that demonstrates the application of the system is also included. The case study involves a Green Highway project located in a highly urbanized area within the Anacostia River watershed of the county. Several best management practices (BMP) such as bioretention, filter vegetative swale, porous paving, and landscape infiltration are proposed for reducing highway runoff and improving water quality. The BMPDSS is used to identify and evaluate various alternatives to determine the most cost-effective types and combinations of BMPs that minimize the highway runoff pollution.

关键词： best management practices decision support system low impact development geographic information system optimization