Littérature scientifique sur le sujet « Shelter location under uncertainty »
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Articles de revues sur le sujet "Shelter location under uncertainty"
Bayram, Vedat, et Hande Yaman. « Shelter Location and Evacuation Route Assignment Under Uncertainty : A Benders Decomposition Approach ». Transportation Science 52, no 2 (mars 2018) : 416–36. http://dx.doi.org/10.1287/trsc.2017.0762.
Texte intégralXiang, Xiaoshu, Ye Tian, Jianhua Xiao et Xingyi Zhang. « A Clustering-Based Surrogate-Assisted Multiobjective Evolutionary Algorithm for Shelter Location Problem Under Uncertainty of Road Networks ». IEEE Transactions on Industrial Informatics 16, no 12 (décembre 2020) : 7544–55. http://dx.doi.org/10.1109/tii.2019.2962137.
Texte intégralCelik, Erkan. « Analyzing the Shelter Site Selection Criteria for Disaster Preparedness Using Best–Worst Method under Interval Type-2 Fuzzy Sets ». Sustainability 16, no 5 (4 mars 2024) : 2127. http://dx.doi.org/10.3390/su16052127.
Texte intégralTrivedi, Ashish, et Amol Singh. « A multi-objective approach for locating temporary shelters under damage uncertainty ». International Journal of Operational Research 38, no 1 (2020) : 31. http://dx.doi.org/10.1504/ijor.2020.10027955.
Texte intégralTrivedi, Ashish, et Amol Singh. « A multi-objective approach for locating temporary shelters under damage uncertainty ». International Journal of Operational Research 38, no 1 (2020) : 31. http://dx.doi.org/10.1504/ijor.2020.106359.
Texte intégralGalemba, Rebecca, Katie Dingeman, Kaelyn DeVries et Yvette Servin. « Paradoxes of Protection : Compassionate Repression at the Mexico–Guatemala Border ». Journal on Migration and Human Security 7, no 3 (29 juillet 2019) : 62–78. http://dx.doi.org/10.1177/2331502419862239.
Texte intégralOzbay, Eren, Özlem Çavuş et Bahar Y. Kara. « Shelter site location under multi-hazard scenarios ». Computers & ; Operations Research 106 (juin 2019) : 102–18. http://dx.doi.org/10.1016/j.cor.2019.02.008.
Texte intégralBayram, Vedat, et Hande Yaman. « A stochastic programming approach for Shelter location and evacuation planning ». RAIRO - Operations Research 52, no 3 (juillet 2018) : 779–805. http://dx.doi.org/10.1051/ro/2017046.
Texte intégralAlumur, Sibel A., Stefan Nickel et Francisco Saldanha-da-Gama. « Hub location under uncertainty ». Transportation Research Part B : Methodological 46, no 4 (mai 2012) : 529–43. http://dx.doi.org/10.1016/j.trb.2011.11.006.
Texte intégralLi, Anna C. Y., Linda Nozick, Ningxiong Xu et Rachel Davidson. « Shelter location and transportation planning under hurricane conditions ». Transportation Research Part E : Logistics and Transportation Review 48, no 4 (juillet 2012) : 715–29. http://dx.doi.org/10.1016/j.tre.2011.12.004.
Texte intégralThèses sur le sujet "Shelter location under uncertainty"
Resseguier, Valentin. « Mixing and fluid dynamics under location uncertainty ». Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S004/document.
Texte intégralThis thesis develops, analyzes and demonstrates several valuable applications of randomized fluid dynamics models referred to as under location uncertainty. The velocity is decomposed between large-scale components and random time-uncorrelated small-scale components. This assumption leads to a modification of the material derivative and hence of every fluid dynamics models. Through the thesis, the mixing induced by deterministic low-resolution flows is also investigated. We first applied that decomposition to reduced order models (ROM). The fluid velocity is expressed on a finite-dimensional basis and its evolution law is projected onto each of these modes. We derive two types of ROMs of Navier-Stokes equations. A deterministic LES-like model is able to stabilize ROMs and to better analyze the influence of the residual velocity on the resolved component. The random one additionally maintains the variability of stable modes and quantifies the model errors. We derive random versions of several geophysical models. We numerically study the transport under location uncertainty through a simplified one. A single realization of our model better retrieves the small-scale tracer structures than a deterministic simulation. Furthermore, a small ensemble of simulations accurately predicts and describes the extreme events, the bifurcations as well as the amplitude and the position of the ensemble errors. Another of our derived simplified model quantifies the frontolysis and the frontogenesis in the upper ocean. This thesis also studied the mixing of tracers generated by smooth fluid flows, after a finite time. We propose a simple model to describe the stretching as well as the spatial and spectral structures of advected tracers. With a toy flow but also with satellite images, we apply our model to locally and globally describe the mixing, specify the advection time and the filter width of the Lagrangian advection method, as well as the turbulent diffusivity in numerical simulations
Haddad, Marcel Adonis. « Nouveaux modèles robustes et probabilistes pour la localisation d'abris dans un contexte de feux de forêt ». Electronic Thesis or Diss., Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLD021.
Texte intégralThe location of shelters in different areas threatened by wildfires is one of the possible ways to reduce fatalities in acontext of an increasing number of catastrophic and severe forest fires. The problem is basically to locate p sheltersminimizing the maximum distance people will have to cover to reach the closest accessible shelter in case of fire. Thelandscape is divided in zones and is modeled as an edge-weighted graph with vertices corresponding to zones andedges corresponding to direct connections between two adjacent zones. Each scenario corresponds to a fire outbreak ona single zone (i.e., on a vertex) with the main consequence of modifying evacuation paths in two ways. First, an evacuationpath cannot pass through the vertex on fire. Second, the fact that someone close to the fire may have limited choice, ormay not take rational decisions, when selecting a direction to escape is modeled using a new kind of evacuation strategy.This evacuation strategy, called Under Pressure, induces particular evacuation distances which render our model specific.We propose two problems with this model: the Robust p-Center Under Pressure problem and the Probabilistic p-CenterUnder Pressure problem. First we prove hardness results for both problems on relevant classes of graphs for our context.In addition, we propose polynomial exact algorithms on simple classes of graphs and we develop mathematical algorithmsbased on integer linear programming
Grannan, Benjamin. « Dispatch, Delivery, and Location Logistics for the Aeromedical Evacuation of Time-Sensitive Military Casualties Under Uncertainty ». VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3536.
Texte intégralKurdi, Mohammad H. « Robust multicriteria optimization of surface location error and material removal rate in high-speed milling under uncertainty ». [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011626.
Texte intégralTheodoridis, Constantinos. « Strategic retail location decision-making under uncertainty : an application of complexity theory in the Greek retailing sector ». Thesis, Manchester Metropolitan University, 2014. http://e-space.mmu.ac.uk/652/.
Texte intégralMeeyai, Sutthipong. « A Hybrid Approach for The Design of Facility Location and Supply Chain Network Under Supply and Demand Uncertainty : A Systematic Review ». Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4673.
Texte intégralAshuri, Baabak. « A Real Options Approach to Modeling Investments in Competitive, Dynamic Retail Markets ». Diss., Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24608.
Texte intégralSiddiq, Auyon. « Robust Facility Location under Demand Location Uncertainty ». Thesis, 2013. http://hdl.handle.net/1807/42932.
Texte intégralHajizadeh, Saffar Iman. « Problems in Supply Chain Location and Inventory under Uncertainty ». Thesis, 2010. http://hdl.handle.net/1807/24764.
Texte intégralMarques, Maria do Céu Lourenço. « Dynamic location problems under uncertainty : models and optimization techniques ». Doctoral thesis, 2015. http://hdl.handle.net/10316/28525.
Texte intégralThis thesis is devoted to mathematical modelling and solution techniques for dynamic facility location problems under uncertainty. The uncertainty regarding the evolution of important problems' parameters along the planning horizon, such as setup and assignment costs, as well as level or location of demand, is explicitly incorporated into the dynamic models through a finite and discrete set of possible scenarios. In the present work we first propose a two-stage stochastic model for the uncapacitated problem. The first decisions to be made are the strategic ones, where and when to locate the facilities throughout the planning horizon. The second-stage decisions refer to the assignment of the existing customers to the open facilities over the whole planning horizon under each possible scenario. As opposite to location decisions, that must be made here and now and should be valid for all possible future scenarios, assignment can be decided after the uncertainty has been resolved and thus can be adjusted in each time period to each possible scenario. The objective is to find a solution that minimizes the expected total cost over all possible scenarios. This model is then extended to other situations, recognizing that other features should be included in the mathematical model to be able to generate other possible solutions. A set of robust constraints is incorporated into that model, that in spite of restricting the set of admissible solutions, it offers more informed and robust solutions under uncertainty. A multi-objective problem wherein each scenario gives rise to an objective is then developed, and relations with other known problems are established as well. For this latter model, requirements about scenarios probabilities or risk profiles are dropped. Within this context, it is emphasized that the Decision Maker will have a better picture of the compromises that exist among the possible scenarios. In terms of models, we conclude with several extensions considering capacitated facilities. The possibility of unmet demand appears naturally in this class of problems, giving rise to other interesting and challenging questions. We propose and discuss both mono and multi-objective approaches. We proceed with the description of the solution techniques that have been developed to tackle the uncapacitated problems. First we present a primal-dual heuristic approach inspired on classical works and a branch&bound scheme integrating this same heuristic. Afterwards, a Lagrangean relaxation approach developed to tackle the problem with robust constraints is detailed. The calculation of non-dominated solutions for the multi-objective problem is discussed and illustrated. Finally, as the models and algorithms were tested over sets of randomly generated problems, the computational experiments and results obtained are provided including comparisons with general solvers. The results of this work aim to help Decision Makers in the difficult process of decision making when dealing with location problems under uncertainty, and thus should be interpreted as decision support tools.
Esta tese versa sobre modelação matemática e algoritmos de resolução de problemas de localização dinâmica em contextos de incerteza. A incerteza acerca de como importantes parâmetros dos problemas irão evoluir ao longo do tempo, tais como custos de instalação de serviços e de afetação, localização ou nível da procura, é explicitamente incorporada nos modelos dinâmicos através de um conjunto finito e discreto de cenários. Na presente dissertação, propomos em primeiro lugar um modelo estocástico de duas fases para o problema de localização sem restrições de capacidades. As primeiras decisões a serem tomadas são as estratégicas, onde e quando localizar os serviços ao longo do horizonte temporal. As decisões de segunda fase referem-se à afetação dos clientes com procura aos serviços abertos ao longo do horizonte temporal para todos os cenários possíveis. Ao contrário das decisões de localização, tomadas no presente e válidas para todos os futuros possíveis, as decisões de afetação podem ser tomadas após a realização da incerteza e ajustadas em cada período temporal a cada cenário. O objetivo do problema é encontrar uma solução que minimize o custo total esperado para todos os cenários possíveis. Este modelo é depois alargado a outras situações, reconhecendo-se que outras características devem ser incluídas no modelo de modo a gerar outras soluções para o problema. Um conjunto de restrições de robustez é incorporado no modelo que, apesar de restringir o conjunto de soluções admissíveis, oferece soluções mais informadas e robustas em situações de incerteza. Um problema multi-objetivo em que cada cenário origina um objetivo é depois apresentado, assim como relações com outros problemas conhecidos. Requisitos acerca das probabilidades associadas aos cenários ou acerca de perfis de risco são desnecessários. É ainda sublinhado que neste contexto o Agente de Decisão terá um melhor retrato dos compromissos existentes entre os possíveis cenários. Em termos de modelos, concluímos com várias extensões considerando serviços com capacidades limitadas. A possibilidade de procura insatisfeita surge naturalmente nesta classe de problemas, dando lugar a outras interessantes e desafiantes questões. Propomos e discutimos abordagens mono e multi-objetivo. Procedemos à descrição dos algoritmos construídos para resolução dos problemas sem restrições de capacidades. Apresentamos uma heurística primal-dual inspirada em abordagens clássicas e um algoritmo branch&bound que integra aquela heurística. Uma técnica usando relaxação Lagrangeana é depois detalhada para resolução do problema com as restrições de robustez. O cálculo de soluções não dominadas para o problema multi-objetivo é discutido e ilustrado com um exemplo. Finalmente, como tanto os modelos como os algoritmos foram testados com instâncias geradas aleatoriamente, as experiências e resultados computacionais são apresentados, incluindo comparações com general solvers. Os resultados deste trabalho pretendem ajudar os Agentes de Decisão no difícil processo de decisão perante problemas de localização em contexto de incerteza, e assim devem ser interpretados como ferramentas de apoio à decisão.
Livres sur le sujet "Shelter location under uncertainty"
Saldanha-da-Gama, Francisco, et Shuming Wang. Facility Location Under Uncertainty. Cham : Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55927-3.
Texte intégralChapitres de livres sur le sujet "Shelter location under uncertainty"
Correia, Isabel, et Francisco Saldanha-da-Gama. « Facility Location Under Uncertainty ». Dans Location Science, 185–213. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32177-2_8.
Texte intégralCorreia, Isabel, et Francisco Saldanha da Gama. « Facility Location Under Uncertainty ». Dans Location Science, 177–203. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13111-5_8.
Texte intégralPatan, Maciej. « Sensor Location under Parametric and Location Uncertainty ». Dans Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems, 183–206. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28230-0_7.
Texte intégralTaherkhani, Gita, et Sibel A. Alumur. « Hub Location Models Under Uncertainty ». Dans International Series in Operations Research & ; Management Science, 337–54. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32338-6_13.
Texte intégralTissot, Gilles, Étienne Mémin et Quentin Jamet. « Stochastic Compressible Navier–Stokes Equations Under Location Uncertainty ». Dans Mathematics of Planet Earth, 293–319. Cham : Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40094-0_14.
Texte intégralTucciarone, Francesco L., Etienne Mémin et Long Li. « Primitive Equations Under Location Uncertainty : Analytical Description and Model Development ». Dans Mathematics of Planet Earth, 287–300. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18988-3_18.
Texte intégralMalmi, Eric, Arno Solin et Aristides Gionis. « The Blind Leading the Blind : Network-Based Location Estimation Under Uncertainty ». Dans Machine Learning and Knowledge Discovery in Databases, 406–21. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23525-7_25.
Texte intégralFigueroa–García, Juan Carlos, Carlos Franco et Roman Neruda. « An Optimization Model for Location-Allocation of Health Services Under Uncertainty ». Dans Computational Intelligence Methodologies Applied to Sustainable Development Goals, 97–108. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97344-5_7.
Texte intégralDias, Joana M., et Maria do Céu Marques. « A Multiobjective Approach for a Dynamic Simple Plant Location Problem under Uncertainty ». Dans Computational Science and Its Applications – ICCSA 2014, 60–75. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09129-7_5.
Texte intégralLiu, Yang, Yun Yuan, Yi Chen, Lingxiao Ruan et Hao Pang. « A Chance Constrained Goal Programming Model for Location-Routing Problem Under Uncertainty ». Dans LISS 2013, 105–16. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40660-7_15.
Texte intégralActes de conférences sur le sujet "Shelter location under uncertainty"
Yardimci, Y., et J. A. Cadzow. « Direction-of-arrival estimation under sensor location uncertainty ». Dans Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319657.
Texte intégralThi, Nguyen Truong, Phan Thi Kim Phung et Tran Thi Tham. « Optimizing Warehouse Storage Location Assignment Under Demand Uncertainty ». Dans 2020 5th International Conference on Green Technology and Sustainable Development (GTSD). IEEE, 2020. http://dx.doi.org/10.1109/gtsd50082.2020.9303113.
Texte intégralQing Ye, Jianshe Song, Zhenglei Yang et Lianfeng Wang. « Emergency vehicle location model and algorithm under uncertainty ». Dans 2011 2nd IEEE International Conference on Emergency Management and Management Sciences (ICEMMS). IEEE, 2011. http://dx.doi.org/10.1109/icemms.2011.6015604.
Texte intégralVitale, Christian, Panayiotis Kolios et Georgios Ellinas. « Intersection Crossing with Connected Autonomous Vehicles under Location Uncertainty ». Dans GLOBECOM 2020 - 2020 IEEE Global Communications Conference. IEEE, 2020. http://dx.doi.org/10.1109/globecom42002.2020.9322403.
Texte intégralWu, Pengcheng, Junfei Xie et Jun Chen. « Safe Path Planning for Unmanned Aerial Vehicle under Location Uncertainty ». Dans 2020 IEEE 16th International Conference on Control & Automation (ICCA). IEEE, 2020. http://dx.doi.org/10.1109/icca51439.2020.9264542.
Texte intégralLiu, Liping, et Zipeng Yi. « Robust Model for Multimodal Location of the Hazmat under Uncertainty ». Dans 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016). Paris, France : Atlantis Press, 2016. http://dx.doi.org/10.2991/aiie-16.2016.5.
Texte intégralRen, Ming_ming, Chao Yang et Bo He. « An Integrated Model and Algorithm for Facility Location under Uncertainty ». Dans Third International Conference on Natural Computation (ICNC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icnc.2007.228.
Texte intégralAanonsen, S. I., A. L. Eide, L. Holden et J. O. Aasen. « Optimizing Reservoir Performance Under Uncertainty with Application to Well Location ». Dans SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 1995. http://dx.doi.org/10.2118/30710-ms.
Texte intégralZhai, Junda, et Guangquan Lu. « Uncertainty Estimation of Location Information under Vehicle-Vehicle Cooperative Control ». Dans 18th COTA International Conference of Transportation Professionals. Reston, VA : American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784481523.007.
Texte intégralRanasinghe, Champika, Nicholas Schiestel et Christian Kray. « Visualising Location Uncertainty to Support Navigation under Degraded GPS Signals ». Dans MobileHCI '19 : 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, NY, USA : ACM, 2019. http://dx.doi.org/10.1145/3338286.3340128.
Texte intégralRapports d'organisations sur le sujet "Shelter location under uncertainty"
Xepapadeas, Anastasios. Environmental Policy and Firm Behavior : Abatement Investment and Location Decisions Under Uncertainty and Irreversibility. Cambridge, MA : National Bureau of Economic Research, août 1999. http://dx.doi.org/10.3386/t0243.
Texte intégralKingston, A. W., A. Mort, C. Deblonde et O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329797.
Texte intégralLiu et Nixon. L52305 Probabilistic Analysis of Pipeline Uplift Resistance. Chantilly, Virginia : Pipeline Research Council International, Inc. (PRCI), juin 2010. http://dx.doi.org/10.55274/r0000002.
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