A Clustering-based Location Allocation Method for Delivery Sites under Epidemic Situations

To address the poor performance of commonly used intelligent optimization algorithms in solving location problems—specifically regarding effectiveness,efficiency,and stability—this study proposes a novel location allocation method for the delivery sites to deliver daily necessities during epidemic quarantines.After establishing the optimization objectives and constraints,we developed a relevant mathematical model based on the collected data and utilized traditional intelligent optimization algorithms to obtain Pareto optimal solutions.Building on the characteristics of these Pareto front solutions,we introduced an improved clustering algorithm and conducted simulation experiments using data from Changchun City.The results demonstrate that the proposed algorithm outperforms traditional intelligent optimization algorithms in terms of effectiveness,efficiency,and stability,achieving reductions of approximately 12%and 8%in time and labor costs,respectively,compared to the baseline algorithm.

基于CDIO模式的人工智能赋能混合式教学方法

针对当前混合式教学方法容易忽视创新实践能力培养的问题,该文结合CDIO工程教育模式,提出人工智能赋能的线上线下混合式教学方法。该文基于线下授课为教学主线,线上虚拟实验为创新实践环节的教学模式,结合人工智能系统与学习分析等技术为教学中的创新实践环节赋能,进一步丰富课程资源、提升学习体验、提高教学质量。该文以寻源算法学习为例,深入开展混合式教学方法在培养学生创新实践能力、促进学习参与度与成就感、发展量化分析评价方法中的应用与实践,并为相关课程提供可资借鉴的混合式教学实施方案。

双碳背景下的城市垃圾智慧收运调度优化与应用研究

目前,我国城市生活垃圾产生量逐年攀升,2021年城市生活垃圾产生量高达27 097.2万t,但现有收运模式难以满足垃圾清运量需求。目前我国垃圾收运环节存在的问题主要包括:(1)中转站点服务能力弱,垃圾清运不及时,环境二次污染严重。(2)收运车辆运行成本高,亏载、走回头路现象严重,总体能耗高。(3)收运方案智慧程度低,垃圾资源化利用效率低。针对上述问题,本团队研发了智慧环卫数字化运维系统。该系统实现了集垃圾收运网络分区重构、车辆供需匹配、路径动态优化为一体的系统功能。力求生态环境效益、社会效益和经济效益,稳步推进“无废城市”建设,促进城市绿色转型。