A Globalized Robust Optimization Approach of Dynamic Network Design Problem With Demand Uncertainty

被引:4
作者
Zhao, Fangwei [1 ]
Sun, Hua [2 ]
Zhao, Fangxia [3 ]
Zhang, Hong [1 ]
Li, Tongfei [4 ]
机构
[1] China Acad Railway Sci Corp Ltd, Met & Chem Res Inst, Beijing 100081, Peoples R China
[2] Gome Share Beijing Network Technol Corp Ltd, Beijing 100016, Peoples R China
[3] China Acad Railway Sci Corp Ltd, Inst Comp Technol, Beijing 100081, Peoples R China
[4] Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
关键词
Cell transmission model; demand uncertainty; globalized robust optimization; network design problem; non-holding back; CELL TRANSMISSION MODEL; TRAFFIC ASSIGNMENT; PROGRAMMING-PROBLEMS; SYSTEM;
D O I
10.1109/ACCESS.2019.2933540
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a globalized robust optimization approach for a network design problem explicit incorporating traffic dynamics and demand uncertainty. In particular, a non-holding back cell transmission model (CTM) based network design problem of linear programming type is considered to describe dynamic traffic flows, and the normal range of the uncertain demand is assumed to be a box set, i.e., the uncertain demand outside box set is allowed. The major contribution of this paper is to formulate such a globalized robust network design problem as a tractable linear programming model and demonstrate the model robustness and flexibility by comparing its solution performance with the robust solution from the usual robust model and the adjustable robust solution from the adjustable robust model, respectively. A numerical experiment is conducted to demonstrate that the modeling advantage of the globalized robust optimization in terms of solution quality. The proposed globalized robust optimization approach may provide useful insights and have broader applicability in traffic management and traffic planning problems under uncertainty.
引用
收藏
页码:115734 / 115748
页数:15
相关论文
共 60 条
[1]   Robust convex optimization [J].
Ben-Tal, A ;
Nemirovski, A .
MATHEMATICS OF OPERATIONS RESEARCH, 1998, 23 (04) :769-805
[2]   Robust solutions of Linear Programming problems contaminated with uncertain data [J].
Ben-Tal, A ;
Nemirovski, A .
MATHEMATICAL PROGRAMMING, 2000, 88 (03) :411-424
[3]   Extending scope of robust optimization: Comprehensive robust counterparts of uncertain problems [J].
Ben-Tal, A ;
Boyd, S ;
Nemirovski, A .
MATHEMATICAL PROGRAMMING, 2006, 107 (1-2) :63-89
[4]   Adjustable robust solutions of uncertain linear programs [J].
Ben-Tal, A ;
Goryashko, A ;
Guslitzer, E ;
Nemirovski, A .
MATHEMATICAL PROGRAMMING, 2004, 99 (02) :351-376
[5]   Robust optimization - methodology and applications [J].
Ben-Tal, A ;
Nemirovski, A .
MATHEMATICAL PROGRAMMING, 2002, 92 (03) :453-480
[6]   Robust solutions of uncertain linear programs [J].
Ben-Tal, A ;
Nemirovski, A .
OPERATIONS RESEARCH LETTERS, 1999, 25 (01) :1-13
[7]   Globalized Robust Optimization for Nonlinear Uncertain Inequalities [J].
Ben-Tal, Aharon ;
Brekelmans, Ruud ;
den Hertog, Dick ;
Vial, Jean-Philippe .
INFORMS JOURNAL ON COMPUTING, 2017, 29 (02) :350-366
[8]   Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains [J].
Ben-Tal, Aharon ;
Do Chung, Byung ;
Mandala, Supreet Reddy ;
Yao, Tao .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2011, 45 (08) :1177-1189
[9]   Robust multi-echelon multi-period inventory control [J].
Ben-Tal, Aharon ;
Golany, Boaz ;
Shtern, Shimrit .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 199 (03) :922-935
[10]   The price of robustness [J].
Bertsimas, D ;
Sim, M .
OPERATIONS RESEARCH, 2004, 52 (01) :35-53