主讲嘉宾：储诚斌 教授

讲座时间：2024年5月30日（周四）15:00

讲座地点：重庆大学B区经济与工商管理学院101报告厅

嘉宾简介：

储诚斌教授现为法国艾菲尔大学、福州大学教授，国家级人才。2006至2011年，西安交通大学海外讲座教授﹑工业工程系海外系主任；2011至2018年任同济大学讲座教授﹑讲座研究员；2017年入选陕西省人才计划在西北工业大学工作。

储教授于1985年毕业于合肥工业学电气工程系工业自动化专业,于1990年以优异成绩获得梅斯大学博士学位。此后，他继续在法国国家信息及自动化研究院工作。1992年被聘为该院终身研究员。他于1995年取得独立指导博士生资格。1996年入盟特鲁瓦工业大学并负责创建和领导工业系统优化实验室。2008至2017年在巴黎中央理工大学（Ecole Centrale Paris，现巴黎-萨克雷大学中央理工-高等电力学院，CentraleSupélec Université Paris-Saclay）,主持由家乐福﹑达能﹑路易威登、赛峰、标致雪铁龙集团等跨国公司赞助的供应链管理讲席职位。

储教授的研究领域集中在生产和物流系统的优化，包括采购管理、可靠性分析与配置、系统维护策略优化、交通运输、切材等方面。迄今为止，他已发表专著3部，200多篇文章被国际期刊发表或接收，其中2篇文章荣获相关期刊的最佳论文奖，3篇论文在国际学术会议获奖。他承担过20多项由欧盟、法国中央和地方政府或企业资助的研究项目，总经费近1000万欧元。他的研究成果在数十家各种规模和不同行业的企业得到应用，并创造巨大经济和社会效益。由于他在理论创新及实际应用方面的突出贡献，他早在1996年就荣获法国运筹学和辅助决策领域的最高奖项Robert Faure一等奖。

讲座摘要：

In this talk, we consider freight transport in urban areas using passenger rail networks as an environment-friendly alternative to current predominantly fossil-fueled trucks. We focus on designing an effective and robust method based on genetic algorithm. The problem is mathematically formulated into a mixed-integer linear program. We prove that as long as a parcel-to-train assignment is known, it takes a polynomial time to check whether this assignment can lead to a feasible solution and, if yes, solve the remaining problem by transforming it into computing the longest distances in a digraph. This result makes it possible to only consider parcel-to-train assignment variables in chromosomes, while efficiently determining the values of the other variables in fitness evaluation. In order to achieve robustness regarding all instances, the control parameters of the genetic algorithm are set with Taguchi method. Computational results show that the method developed in this way is very effective. For small-size instances, it yields optimal solutions within considerably shorter computation times than a commonplace optimization solver does. For large-size instances, it outperforms such a solver, not only providing much higher-quality solutions but also consuming much shorter computation times. This method thus meets very well operational requirements where high-quality solutions are expected while computation time is very limited. We also show that the problem as well as the pricing problem in the branch-and-price framework can be solved with Benders decomposition where the slave problem can be exactly solved with Bellman-Ford method.