加入支持让我们有继续维护的动力!会员畅享查看所有预告
立即购买
电子科技大学殷允强教授学术讲座
- 来源:
- 学校官网
- 收录时间:
- 2024-12-12 09:16:28
- 时间:
- 2024-12-17 09:00:00
- 地点:
- B校区经管学院101报告厅
- 报告人:
- 殷允强 教授
- 学校:
- -/-
- 关键词:
- dial-a-ride, mean-variance risk index, uncertain travel time, optimization, non-emergency medical transportation
- 简介:
- Motivated by real challenges faced by a non-emergency medical transportation service provider, we study a selective dial-a-ride problem with uncertain travel time and aim to optimize the service coverage subject to some service quality requirements. To manage violations of service requirements, we introduce a mean-variance risk index. This index effectively controls both the likelihood and magnitude of such violations. Furthermore, it enables the development of practical optimization models. We construct a collective risk model specifically for dial-a-ride optimization and devise efficient branch-and-price-and-cut algorithms to handle the resulting nonlinear integer programs. To verify the efficiency of our proposed models and algorithm, we perform comprehensive experiments using both synthetic and real data. Much of the dial-a-ride literature focuses on deterministic travel times. We highlight the importance of considering uncertain travel times. We have developed practical models and algorithms for non-emergency medical transportation. Our approach has proven to lead to a greater number of served requests with improved quality. As such, we demonstrate the practical value of advanced optimization techniques when dealing with real-world uncertainty.
- -/- 13
报告介绍:
Motivated by real challenges faced by a non-emergency medical transportation service provider, we study a selective dial-a-ride problem with uncertain travel time and aim to optimize the service coverage subject to some service quality requirements. To manage violations of service requirements, we introduce a mean-variance risk index. This index effectively controls both the likelihood and magnitude of such violations. Furthermore, it enables the development of practical optimization models. We construct a collective risk model specifically for dial-a-ride optimization and devise efficient branch-and-price-and-cut algorithms to handle the resulting nonlinear integer programs. To verify the efficiency of our proposed models and algorithm, we perform comprehensive experiments using both synthetic and real data. Much of the dial-a-ride literature focuses on deterministic travel times. We highlight the importance of considering uncertain travel times. We have developed practical models and algorithms for non-emergency medical transportation. Our approach has proven to lead to a greater number of served requests with improved quality. As such, we demonstrate the practical value of advanced optimization techniques when dealing with real-world uncertainty.
报告人介绍:
殷允强,电子科技大学教授、博士生导师、管理科学与电子商务系主任,入选国家级青年人才计划、四川省杰青。2014-2023连续10年入选Elsevier 中国高被引学者榜单。主要从事智能决策与优化、生产与物流运作管理等方面的研究。主持国家自然科学基金项目5项,国家社科重大项目子课题1项,四川省自然科学基金重点项目1项等。以第一作者或通讯作者在JOM、TRB、NRL、EJOR、Omega、IEEE Trans等国际期刊发表SCI论文70余篇,出版学术专著2部、教材《整数规划:基础、扩展及应用》1本,授权国家发明专利5项。兼任中国管理科学与工程学会理事、中国双法研究会船海经济管理专业委员会副理事长、中国系统工程学会决策科学专业委员会副主任委员、中国双法研究会智能决策与博弈分会秘书长等职,同时担任SCI期刊Complex & Intelligent Systems副主编、International Journal of General Systems编委、系统科学与数学编委以及International Journal of Production Research、控制与决策等多个期刊的(Leader) Guest Editor。