Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment

被引:8
|
作者
Xu, Jiuping [1 ,2 ]
Gang, Jun [2 ]
Lei, Xiao [3 ]
机构
[1] Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610064, Peoples R China
[2] Sichuan Univ, Uncertainty Decis Making Lab, Chengdu 610064, Peoples R China
[3] China Three Gorges Corp, Yichang 443002, Peoples R China
基金
美国国家科学基金会;
关键词
HAZARDOUS MATERIALS TRANSPORTATION; ROAD NETWORK; RISK; PERFORMANCE; ALGORITHM; SETS;
D O I
10.1155/2013/517372
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes.
引用
收藏
页数:22
相关论文
共 50 条
  • [41] Resilient Transportation Network Design under Uncertain Link Capacity Using a Trilevel Optimization Model
    Rahdar, Mohammad
    Wang, Lizhi
    Dong, Jing
    Hu, Guiping
    JOURNAL OF ADVANCED TRANSPORTATION, 2022, 2022
  • [42] Resilient Transportation Network Design under Uncertain Link Capacity Using a Trilevel Optimization Model
    Rahdar, Mohammad
    Wang, Lizhi
    Dong, Jing
    Hu, Guiping
    Journal of Advanced Transportation, 2022, 2022
  • [43] A note on "Transportation problem under interval-valued intuitionistic fuzzy environment"
    Mishra, Akansha
    Kumar, Amit
    Khan, Meraj Ali
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2019, 37 (01) : 897 - 900
  • [44] Emergency Service Model Analysis to Heterogeneous Network Environment
    Liao, Huei-Min
    Chang, Kai-Di
    Chen, Chi-Yuan
    Chen, Jiann-Liang
    Chao, Han-Chieh
    Chiang, Hua-Pei
    2012 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2012, : 1027 - 1031
  • [45] An integrated model of facility location and transportation network design
    Melkote, S
    Daskin, MS
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2001, 35 (06) : 515 - 538
  • [46] A bilevel flow model for hazmat transportation network design
    Bianco, Lucio
    Caramia, Massimiliano
    Giordani, Stefano
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2009, 17 (02) : 175 - 196
  • [47] Fuzzy modeling in response surface method for complex computer model based design optimization
    Xu, Ruoning
    Dong, Zuomin
    PROCEEDINGS OF THE 2006 IEEE/ASME INTERNATIONAL CONFERENCE ON MECHATRONIC AND EMBEDDED SYSTEMS AND APPLICATIONS, 2006, : 338 - +
  • [48] Adaptive Chebyshev Neural Network Control for Ventilator Model under the Complex Mine Environment
    Liu, Ranhui
    Hu, Xinyan
    Zhang, Chengyuan
    Liu, Chuanxi
    COMPLEXITY, 2020, 2020
  • [49] A multi-objective transportation model under neutrosophic environment
    Rizk-Allah, Rizk M.
    Hassanien, Aboul Ella
    Elhoseny, Mohamed
    COMPUTERS & ELECTRICAL ENGINEERING, 2018, 69 : 705 - 719
  • [50] Reliable design of a logistics network under uncertainty: A fuzzy possibilistic-queuing model
    Vahdani, Behnam
    Tavakkoli-Moghaddam, Reza
    Jolai, Fariborz
    APPLIED MATHEMATICAL MODELLING, 2013, 37 (05) : 3254 - 3268