主题：Towardsan Adaptive Memory Programming Approach for the Robust Capacitated VehicleRouting Problem    

报告人：PanagiotisP. Repoussis, PhD，AssistantProfessor in Operations (tenure track)，STEVENSINSTITUTE of TECHNOLOGY

Panagiotis P. Repoussis，博士，史蒂文斯理工学院技术管理学院助理教授，毕业于雅典经济与商业大学，获管理科学与技术方向博士学位，主要研究兴趣为：Quantitative analysis, modeling andoptimization methods for a variety of problems in transportation anddistribution logistics; network design; manufacturing and service operation management;terminal management; production scheduling; vehicle routing and scheduling。曾经在TransportationScience、European Journal of Operations Research、Optimization Letters等本领域知名学术期刊上发表十多篇学术论文。

报告摘要：Wepresent an Adaptive Memory Programming (AMP) meta heuristic to address theRobust Capacitated Vehicle Routing Problem under demand uncertainty. Contraryto its deterministic counterpart, the robust formulation allows for uncertaincustomer demands, and the objective is to determine a minimum cost deliveryplan that is feasible for all demand realizations within a prespecieduncertainty set. A crucial step in our heuristic is to verify the robustfeasibility of a candidate route. For generic uncertainty sets, this step requiresthe solution of a convex optimization problem, which becomes computationallyprohibitive for large instances. We present two classes of uncertainty sets forwhich route feasibility can be established much more eciently. While we discussour implementation in the context of the AMP framework, our techniques readilyextend to other meta heuristics. Computational studies on standard literaturebenchmarks with up to 483 customers and 38 vehicles demonstrate that theproposed approach is able to quickly provide high quality solutions. In theprocess, we obtain new best solutions for a total of 123 benchmark instances.
    主持人：贾传亮 副教授党总支副书记

时 间：2014年5月14日14:00-16:00
    地点：12BET学术会堂 606 会议室