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数据魔术师
运筹优化及人工智能系列讲座第34期
【活动信息】
题目：鲁棒团队定向问题在震后搜救队调度中的应用
Title: Robust Team Orienteering Problem with Decreasing Profits
主 讲 人: 余沁潇 中国民航大学经济与管理学院讲师
主 持 人: 程春 东北财经大学助理教授
活动时间: 2022年5月30日 下午15:00 - 16:30
讲座语言：中文
主办单位：数据魔术师
直播平台：通过数据魔术师粉丝群发布讲座腾讯会议信息
【主讲人简介】
余沁潇，2021年博士毕业于天津大学管理与经济学部管理科学与工程专业，本硕博均就读于天大经管学部。博士期间曾前往加拿大蒙特利尔大学工学院进行一年期博士生联合培养，主要从事运筹优化算法及其在交通、物流、应急救援管理中的应用研究，研究成果以第一作者身份发表于INFORMS Journal on Computing、European Journal of Operational Research等期刊。
【报告摘要】
This paper studies a robust variant of the teamorienteering problem with decreasing profits (TOP-DP), where a fleet ofvehicles are dispatched to serve customers with decreasing profits in a limitedtime horizon. The service times at customers are assumed to be uncertain, whichare characterized by a budgeted uncertainty set. Our goal is to determine theset of customers to be served and the routes for the fleet of vehicles suchthat the collected profit is maximized; meanwhile, all the planned routesremain feasible for any realization of service times within the uncertaintyset. We propose a tractable robust formulation for the problem, which utilizesdynamic programming recursive equations to calculate the worst-case arrivaltimes at customers along a given route. To solve the robust model, we develop abranch-and-price (B&P) algorithm for exact solutions and a tabu search (TS)algorithm for approximation solutions. Numerical tests show that our B&Palgorithm can solve most instances with 100 customers to optimality within 25minutes and that the TS algorithm can find high-quality solutions within a fewseconds. Moreover, we find that in most cases, the robust solutions cansignificantly reduce the probability of deadline violations in simulation testswith only a slight compromise of profit, compared to the solutions generated bythe deterministic model.
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