Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters.

[1]  Soheyl Khalilpourazari,et al.  Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application , 2019, Ann. Oper. Res..

[2]  Kathryn E. Stecke,et al.  Design, planning, scheduling, and control problems of flexible manufacturing systems , 1985 .

[3]  Malin Song,et al.  Analysis and exploration of damage-reduction measures for flood disasters in China , 2019, Ann. Oper. Res..

[4]  Haijun Wang,et al.  Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake , 2014 .

[5]  Chen Huang,et al.  Microblogging after a major disaster in China: a case study of the 2010 Yushu earthquake , 2011, CSCW.

[6]  V. Uma,et al.  Temporal Sentiment Analysis and Causal Rules Extraction from Tweets for Event Prediction , 2015 .

[7]  Surya Prakash Singh,et al.  Formulating multi-objective stochastic dynamic facility layout problem for disaster relief , 2019, Ann. Oper. Res..

[8]  Zelda B. Zabinsky,et al.  Stochastic optimization of medical supply location and distribution in disaster management , 2010 .

[9]  Fallah-MehdipourElahe,et al.  Extraction of decision alternatives in construction management projects , 2012 .

[10]  Alexander Zipf,et al.  A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management , 2015, Int. J. Geogr. Inf. Sci..

[11]  I-Chin Wu,et al.  Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm , 2017, Health care management science.

[12]  Boni Su,et al.  Integrated simulation method for waterlogging and traffic congestion under urban rainstorms , 2016, Natural Hazards.

[13]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[14]  Hong Zhou,et al.  Multiobjective Location Routing Problem considering Uncertain Data after Disasters , 2017 .

[15]  L. Kalaivani,et al.  Speed control of switched reluctance motor with torque ripple reduction using non-dominated sorting genetic algorithm (NSGA-II) , 2013 .

[16]  Reza Zanjirani Farahani,et al.  A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study , 2017, Ann. Oper. Res..

[17]  Yang Liu,et al.  Design and Implementation of Monitoring and Early Warning System for Urban Roads Waterlogging , 2014, CCTA.

[18]  Shiwei Yu,et al.  A multi-objective decision model for investment in energy savings and emission reductions in coal mining , 2017, Eur. J. Oper. Res..

[19]  Zhao Yan,et al.  Emergency logistics decision support system based on data mining and WebGIS technology , 2012 .

[20]  Eiichi Taniguchi,et al.  Location and Routing Problems of Debris Collection Operation after Disasters with Realistic Case Study , 2014 .

[21]  Malin Song,et al.  Environmental efficiency and economic growth of China: A Ray slack-based model analysis , 2017, Eur. J. Oper. Res..

[22]  Omid Bozorg Haddad,et al.  Extraction of decision alternatives in construction management projects: Application and adaptation of NSGA-II and MOPSO , 2012, Expert Syst. Appl..

[23]  Walter J. Gutjahr,et al.  Modelling beneficiaries’ choice in disaster relief logistics , 2017, Ann. Oper. Res..

[24]  Chinyao Low,et al.  Heuristic solutions to multi-depot location-routing problems , 2002, Comput. Oper. Res..

[25]  Rajan Batta,et al.  Dispatching and routing of emergency vehicles in disaster mitigation using data fusion , 2009 .

[26]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[27]  Cornelia Caragea,et al.  Sentiment analysis during Hurricane Sandy in emergency response , 2017 .

[28]  Linet Özdamar,et al.  A dynamic logistics coordination model for evacuation and support in disaster response activities , 2007, Eur. J. Oper. Res..

[29]  Yutaka Matsuo,et al.  Earthquake shakes Twitter users: real-time event detection by social sensors , 2010, WWW '10.

[30]  Ching-Jung Ting,et al.  A multiple ant colony optimization algorithm for the capacitated location routing problem , 2013 .

[31]  Walter J. Gutjahr,et al.  A math-heuristic for the warehouse location-routing problem in disaster relief , 2014, Comput. Oper. Res..

[32]  Shao-Long Hu,et al.  A scenario planning approach for propositioning rescue centers for urban waterlog disasters , 2015, Comput. Ind. Eng..

[33]  David K. Smith,et al.  Use of location-allocation models in health service development planning in developing nations , 2000, Eur. J. Oper. Res..

[34]  Miao Duoqian,et al.  News Topic Detection Approach on Chinese Microblog , 2012 .

[35]  Mostafa Zandieh,et al.  Bi-objective partial flexible job shop scheduling problem: NSGA-II, NRGA, MOGA and PAES approaches , 2012 .

[36]  S. Shen,et al.  Investigation into pluvial flooding hazards caused by heavy rain and protection measures in Shanghai, China , 2016, Natural Hazards.

[37]  Mao De-hua.  Assessment and analysis of flood-waterlogging disaster condition in Dongting lake region , 2000 .

[38]  Leon Cooper,et al.  AN EFFICIENT HEURISTIC ALGORITHM FOR THE TRANSPORTATION‐LOCATION PROBLEM , 1976 .

[39]  Harpreet Kaur,et al.  Sustainable procurement and logistics for disaster resilient supply chain , 2019, Ann. Oper. Res..

[40]  Dingwei Wang,et al.  Study on Multi-depots Vehicle Transshipment Scheduling Problem and Its Genetic Algorithm and Ant Colony Algorithm Hybrid Optimization , 2016 .

[41]  Vahid Majazi Dalfard,et al.  Two meta-heuristic algorithms for two-echelon location-routing problem with vehicle fleet capacity and maximum route length constraints , 2012, Neural Computing and Applications.

[42]  Leon Cooper,et al.  The Transportation-Location Problem , 1972, Oper. Res..

[43]  Leyuan Shi,et al.  Optimization Based Method for Supply Location Selection and Routing in Large-Scale Emergency Material Delivery , 2011, IEEE Transactions on Automation Science and Engineering.

[44]  Manoj Kumar Tiwari,et al.  Multi-objective process planning and scheduling using controlled elitist non-dominated sorting genetic algorithm , 2015 .

[45]  Abbas Seifi,et al.  A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district , 2015 .

[46]  S. Bandyopadhyay,et al.  Solving multi-objective parallel machine scheduling problem by a modified NSGA-II , 2013 .

[47]  Yong Wang,et al.  A Developed NSGA-II Algorithm for Multi-objective Chiller Loading Optimization Problems , 2016, ICIC.

[48]  Ching-Jung Ting,et al.  A simulated annealing heuristic for the capacitated location routing problem , 2010, Comput. Ind. Eng..

[49]  Seyed Taghi Akhavan Niaki,et al.  Optimizing a bi-objective multi-product EPQ model with defective items, rework and limited orders: NSGA-II and MOPSO algorithms , 2013 .

[50]  Seokcheon Lee,et al.  The Latency Location-Routing Problem , 2016, Eur. J. Oper. Res..

[51]  Xiaojing Liu,et al.  Wargame Simulation Theory and Evaluation Method for Emergency Evacuation of Residents from Urban Waterlogging Disaster Area , 2016, International journal of environmental research and public health.

[52]  Jing Liu,et al.  A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems , 2017 .