Robust alternative fuel refueling station location problem with routing under decision-dependent flow uncertainty

被引:5
|
作者
Mahmutogullari, Ozlem [1 ]
Yaman, Hande [1 ]
机构
[1] Katholieke Univ Leuven, Fac Econ & Business, ORSTAT, B-3000 Leuven, Belgium
关键词
Location; Robust optimization; Decision -dependent uncertainty; Benders reformulation; Alternative fuel vehicles; STOCHASTIC-PROGRAMMING APPROACH; HEURISTIC ALGORITHM; INFRASTRUCTURE DEVELOPMENT; NETWORK; MODEL; OPTIMIZATION; PRICE; FORMULATION; VEHICLES; DESIGN;
D O I
10.1016/j.ejor.2022.07.006
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The refueling station location problem with routing (RSLP-R) is defined as a maximal coverage problem that locates alternative fuel refueling stations (AFSs) on a road network to maximize the refueled alter-native fuel vehicle flows by considering the limited range of vehicles and the willingness of drivers to deviate from their paths for refueling. In this study, we introduce the robust counterpart of RSLP-R us-ing a decision-dependent polyhedral uncertainty set. We model the flow uncertainty set using a hybrid model that comprises a hose model and individual flow bounds. To take into account the fact that vehi-cle flows are affected by AFS deployment decisions in their neighborhoods, we incorporate the decision -dependency notion into the flow uncertainty set. We propose two linear mixed integer programming for-mulations and a Benders reformulation. Our computational experiments on instances based on the road network of Belgium confirm the effectiveness of the reformulation in solving larger instances. We also re-port the results of experiments to assess the value of incorporating uncertainty and decision-dependency into the problem.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码:173 / 188
页数:16
相关论文
共 50 条
  • [1] Mathematical formulations for the multi-period alternative fuel refueling station location problem with routing under decision-dependent flow dynamics
    Mahmutoğulları, Özlem
    Yaman, Hande
    [J]. Transportation Research Part B: Methodological, 2024, 186
  • [2] A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing
    Arslan, Okan
    Karasan, Oya Ekin
    Mahjoub, A. Ridha
    Yaman, Hande
    [J]. TRANSPORTATION SCIENCE, 2019, 53 (04) : 1107 - 1125
  • [3] Refueling-station location problem under uncertainty
    Hosseini, Meysam
    MirHassani, S. A.
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2015, 84 : 101 - 116
  • [4] Distributionally robust facility location problem under decision-dependent stochastic demand
    Basciftci, Beste
    Ahmed, Shabbir
    Shen, Siqian
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2021, 292 (02) : 548 - 561
  • [5] Sustainable generalized refueling station location problem under uncertainty
    Tafakkori, Keivan
    Bozorgi-Amiri, Ali
    Yousefi-Babadi, Abolghasem
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2020, 63
  • [6] OPTIMIZATION UNDER DECISION-DEPENDENT UNCERTAINTY
    Nohadani, Omid
    Sharma, Kartikey
    [J]. SIAM JOURNAL ON OPTIMIZATION, 2018, 28 (02) : 1773 - 1795
  • [7] Robust approximation of chance constrained DC optimal power flow under decision-dependent uncertainty
    Aigner, Kevin-Martin
    Clarner, Jan-Patrick
    Liers, Frauke
    Martin, Alexander
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 301 (01) : 318 - 333
  • [8] Hydrogen refueling station location optimization under uncertainty
    Zhen, Lu
    Wu, Jingwen
    Yang, Zhiyuan
    Ren, Yiran
    Li, Wenxin
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2024, 190
  • [9] A robust optimization method for power systems with decision-dependent uncertainty
    Tan, Tao
    Xie, Rui
    Xu, Xiaoyuan
    Chen, Yue
    [J]. Energy Conversion and Economics, 2024, 5 (03): : 133 - 145
  • [10] A Continuous Deviation-Flow Location Problem for an Alternative-Fuel Refueling Station on a Tree-Like Transportation Network
    Kweon, Sang Jin
    Hwang, Seong Wook
    Ventura, Jose A.
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2017,