糖心vlog专家讲座:Machine learning assisted hyper-heuristics for online combinatorial optimization problems

报告时间20231016日(周一),15:00-16:30

报告地点:物流楼506

主 讲 人: 白瑞斌

报告摘要

In the past decade, considerable advances have been made in the field of computational intelligence and operations research. However, the majority of these optimization approaches have been developed for deterministically formulated problems, the parameters of which are often assumed perfectly predictable prior to problem-solving. In practice, this strong assumption unfortunately contradicts the reality of many real-world problems which are subject to different levels of uncertainties. The solutions derived from these deterministic approaches can rapidly deteriorate during execution due to the over-optimization without explicit consideration of the uncertainties. To address this research gap, two data-driven hyper-heuristic frameworks are investigated. This talk will present the main ideas of the methods and their performance for two combinatorial optimization problems: a real-world container terminal truck routing problem with uncertain service times and the well-known online 2D strip packing problem. The talk shall briefly describe a port digital twin system developed by our team for the purpose of integrated optimization of multiple port operations.

主讲人简介

   白瑞斌,宁波诺丁汉大学计算机科学教授、系主任,博导,宁波市数字港口重点实验室主任,IEEE高级会员,国际SCI Top期刊EJOR编委,SCI Q1期刊 Networks编委。入选浙江省基金杰出青年基金项目,宁波市领军和拔尖人才培养对象,华为军团难题挑战赛火花奖获得者,浙江省计算机学会数字港口专委会主任,宁波市人工智能学会副理事长。NSFC评审专家(优秀、联合基金重点、面上)。研究领域包括智能计算、组合优化、强化学习、数字孪生等,在包括INFORMS JoCIEEE TEVCTR Part BEJOR等期刊和会议发表论文100余篇。作为项目负责人先后申请获批科技项目20余项,科研总经费超过1000万元,培养毕业博士生7名,带领团队研究开发了包括基于n-ToS的集装箱码头自动车辆调度、宁波港区集装箱公路铁路综合运输优化、港口码头智慧大屏、港口数字孪生、汽车零部件环境效益评价(LCA)等软硬件系统5套。部分系统并在宁波港实现了测试和商业应用。

主办单位:集装箱供应链技术教育部工程研究中心


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