Special Session Ⅱ

 

Data-Driven Intelligent Decision-Making and Optimization  (Submission Deadline: June 27, 2026)
数据驱动的智能决策与优化

 

Chair:
Shaojian Qu Nanjing University of Information Science and Technology, China
Keywords:
·  Intelligent Decision-Making (智能决策) ·  Big Data Analytics (大数据分析) ·  Risk Management (风险管理) ·  Group Consensus (群体共识) ·  Optimization Algorithms (优化算法)
Topics:
·  Big Data Analytics-Driven Intelligent Decision-Making: Including multi-source heterogeneous data fusion, real-time streaming data processing, and explainable machine learning for decision support (大数据分析驱动的智能决策：包括多源异构数据融合、实时流数据处理、可解释性机器学习在决策中的应用) ·  Risk Management and Emergency Decision-Making for Complex Systems: Focusing on modeling and optimization for supply chain disruption risks, systemic financial risks, and natural disaster emergency responses (复杂系统的风险管理与应急决策：聚焦于供应链中断风险、金融系统性风险、自然灾害应急响应的建模与优化) ·  Intelligent Optimization and Coordination in Supply Chain Systems: Covering inventory control, logistics path optimization, demand forecasting, and multi-echelon supply chain collaborative decision-making (供应链系统的智能优化与协调：涵盖库存控制、物流路径优化、需求预测、多级供应链协同决策) ·  Portfolio Optimization and Financial Risk Management: Including dynamic asset allocation, risk measurement models, high-frequency trading strategies, and financial time series analysis (投资组合优化与金融风险管理：包括动态资产配置、风险度量模型、高频交易策略、金融时间序列分析) ·  Group Consensus Mechanisms and Applications: Involving multi-attribute group decision-making, opinion dynamics modeling, conflict resolution, and preference analysis in consensus reaching processes (群体共识机制及其应用：涉及多属性群决策、意见演化建模、冲突消解、共识达成过程中的偏好分析) ·  Advances in Decision Science Theory: Such as new methods in multi-criteria decision-making, game theory applications in collaborative control, and behavioral decision theory (决策科学理论的前沿进展：如多准则决策中的新方法、博弈论在协同控制中的应用、行为决策理论) ·  Machine Learning and Data Mining in Managerial Decision-Making: Including recommendation systems, customer behavior analysis, anomaly detection, and credit scoring models (机器学习与数据挖掘在管理决策中的应用：包括推荐系统、客户行为分析、异常检测、信用评分模型) ·  Modeling and Optimization under Uncertainty: Covering fuzzy decision-making, robust optimization, stochastic programming, and interval programming theories and methods (不确定性环境下的建模与优化：涵盖模糊决策、鲁棒优化、随机规划、区间规划等理论与方法)
Summary:
·  This session addresses intelligent decision-making challenges in complex systems (e.g., supply chains, finance, emergency management) within the big data era. Extracting insights from massive data for scientific decisions is a core challenge in management science. It aims to explore novel methods integrating big data analytics, machine learning, and optimization algorithms to enhance decision quality and efficiency in complex environments. Targeted at researchers in management science and engineering, participants will gain insights into latest theoretical breakthroughs and applications, discuss key issues, and identify potential collaboration directions.
·  本专题聚焦于大数据时代复杂系统（如供应链、金融、应急管理）中的智能决策挑战。如何从海量数据中提取有效信息并做出科学决策，是管理科学的的核心问题。专题旨在探讨融合大数据分析、机器学习与优化算法的智能决策新方法，以提升复杂环境下的决策质量与效率。面向管理科学与工程、系统工程等领域的研究人员，参与者将了解本领域最新理论突破与应用成果，探讨关键难题，并获得潜在合作研究方向。