Pith. sign in

REVIEW 3 major objections 4 minor 1 cited by

Recent Advances in Disaster Emergency Response Planning: Integrating Optimization, Machine Learning, and Simulation

T0 review · 3 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read This survey maps the 2019–2024 disaster response planning literature into a three-method taxonomy—optimization models, machine learning, and simulation—and argues that progress comes from combining them.

desk verdict A readable, genuinely useful survey of 2019-2024 disaster response planning research, but its unsystematic sample and a couple of probably-false 'no work exists' claims undercut the trend and gap analysis. read the letter →

arxiv 2505.03979 v1 pith:DIFB4HV5 submitted 2025-05-06 math.OC

Fan Pu , Zihao Li , Yifan Wu , Chaolun Ma , Ruonan Zhao This is my paper · ORCID
classification math.OC MSC 90B0690B5090C1190C15
keywords DisasterEmergencyResponsePlanningOptimizationModelsMachineLearningSimulationEvacuationFacilityLocationCasualtyTransportReliefDistribution
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This survey maps the 2019–2024 research literature on disaster emergency response planning across five operational areas—evacuation, facility location, casualty transport, search and rescue, and relief distribution—and organizes the field by methodology: optimization models, machine learning, and simulation. The authors argue that optimization models remain the cornerstone of planning because they deliver optimal or near-optimal solutions, but they struggle with large-scale, uncertain, and behaviorally complex disasters. Machine learning and simulation, the survey claims, fill those gaps by learning from data and replicating dynamic environments, yet neither offers the analytical guarantees optimization provides. The paper's key contribution is examining how the three methods complement one another, and it concludes with future research directions centered on real-time adaptation, prediction in complex environments, equity, and risk quantification.

What carries the argument

The organizing device is a two-dimensional classification grid: five operational problem areas (evacuation, facility location, casualty transport, search and rescue, relief distribution) crossed with three methodological families (optimization models, machine learning, simulation). The survey uses this grid to classify the selected studies, highlight where a category is empty or sparse—such as machine learning in facility location and simulation in search and rescue—and draw conclusions about where the field is heading. Supporting that grid are formal problem templates that recur across areas, notably the Markov decision process for dynamic dispatch, the orienteering problem and vehicle routing problem for search and relief routing, and location-allocation models for facility placement, which together let the authors compare methods on a common footing.

What would settle it

A systematic, reproducible search of the same databases and time window with explicit inclusion criteria, followed by paper-by-paper counting by method and problem area, would settle the survey's map. If the resulting distribution showed, for instance, a substantial body of machine-learning work in facility location or simulation in search and rescue within the 2019–2024 window, or if the majority of machine-learning papers proved to optimize decisions rather than merely evaluate them, the survey's claimed trends and its stated research gaps would be selection artifacts rather than properties of the field.

Watch

Extended reading notes

Core claim

The central claim is that the 2019–2024 literature on disaster emergency response planning is best understood as a three-way methodological conversation in which optimization, machine learning, and simulation each supply what the others lack. Optimization models—mixed-integer programming, stochastic and robust optimization, Markov decision processes—offer precise, provable solutions but rely on simplifications that lose the dynamism, uncertainty, and human behavior of real disasters. Machine learning, especially reinforcement learning, provides real-time adaptability and pattern recognition from data but faces issues of interpretability, data quality, and generalization. Simulation, particularly agent-based modeling and discrete-event simulation, captures emergent behavior and infrastructure interactions but lacks the analytical rigor to guide decisions directly. The survey demonstrates these complementarities across all five problem areas, noting, for example, that machine learning appears in casualty transport mainly as a solver for MDP-based dispatch, while simulation in facility location captures evacuee behavior that optimization models oversimplify.

Load-bearing premise

The survey's picture of research trends and gaps rests on the assumption that its selected 'representative' studies are a balanced sample of the 2019–2024 literature; if the selection is biased toward certain publishers, problem types, or methods, the conclusions would not generalize.

Editorial extensions

If this is right

  • The taxonomy reveals empty cells—machine learning in facility location and simulation in search and rescue—which the survey treats as notable gaps rather than explored areas.
  • If the map is accurate, the frontier of the field is hybrid: optimization frameworks supplemented by machine learning for real-time decisions and by simulation for realistic evaluation.
  • Reinforcement learning emerges as the dominant machine-learning tool for dynamic dispatch and routing problems, pointing to a convergence on MDP-based formulations across casualty transport, relief distribution, and search and rescue.
  • The review identifies equity and risk aversion as cross-cutting concerns that multi-objective and risk-averse optimization are beginning to address.
  • Simulation and supervised learning currently serve mostly as evaluation tools, not decision optimizers, marking an open problem for future integration with optimization.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper's qualitative mapping implies that publication volume by method is uneven, but the survey does not report counts; a bibliometric follow-up that quantifies the distribution across the five areas and three methods would test whether the perceived gaps are real or an artifact of the representative-study selection.
  • The sparse cells (machine learning in facility location, simulation in search and rescue) may reflect the survey's exclusion of small-scale and non-operational studies; broadening the inclusion criteria could fill those cells and change the claimed trends.
  • The complementarity narrative suggests a concrete testable design: embed a learned surrogate (for example, a neural network predicting evacuee behavior) inside a stochastic optimization loop and compare solution quality and runtime against a pure optimization baseline on the same disaster scenario.
  • The five-area scope could be extended to recovery and public-health emergencies, where the same three-method taxonomy might expose analogous gaps.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. This manuscript is a narrative survey of the 2019–2024 literature on disaster emergency response planning, organized around five operational areas: evacuation, facility location, casualty transport, search and rescue, and relief distribution. Within each area, the authors review work from the perspective of three methodologies—optimization models, machine learning, and simulation—and they close with a set of future research directions. The contribution claimed is a methodological map that clarifies the roles of and synergies among optimization, ML, and simulation in improving emergency response planning.

Significance. If the survey's sampling were systematic, the paper would be a useful resource for researchers entering the field, because it consolidates a large and scattered literature across five problem areas and three methodological traditions. The discussion of integration between ML/simulation and optimization is timely, and the explicit future-directions list (online learning, equity, risk quantification) is sensible. The paper also gives credit to machine-checkable aspects of the reviewed literature, although the survey itself does not contribute new proofs, code, or data. The significance is therefore primarily organizational and pedagogical, which is appropriate for a review journal.

major comments (3)
  1. [Section 1] The statement 'For areas where no relevant studies are available, they will be excluded accordingly, such as machine learning in facility location and simulation in search and rescue' is a checkable empirical claim, and it is likely false for the 2019–2024 window. There exist published works from this period on machine learning integrated with facility location (e.g., demand prediction feeding location-allocation models, and reinforcement learning for location-allocation under uncertainty) and on simulation-based search-and-rescue planning (e.g., agent-based and discrete-event models of search operations). Because the paper's central contribution is to map the methodological landscape, these exclusion claims are load-bearing: if they are wrong, the map omits active research areas and the 'key contribution' about the roles of ML and simulation is incomplete. The authors should either substantiate these exclusions with a documented search (including search strings, databases, and screening results) or correct them by including representative studies.
  2. [Section 1] The survey selection process is not described systematically. The text lists publishers and databases but gives no search strings, date-specific query details, inclusion/exclusion criteria, screening counts, or a definition of 'representative studies.' This would be a presentation issue for a purely descriptive bibliography, but here aggregate conclusions about the field are drawn from the selected set—for example, §2 states 'most optimization models in evacuation research focus on...', §4 states 'MDPs are commonly used...', and §6 states 'robust and stochastic optimization approaches have been developed...'. These are claims about the literature as a whole, but they are supported only by an unenumerated, potentially biased subset. The authors should add a methods paragraph describing their search and screening protocol, and they should either report the number of papers found and included at each stage or explicitly reframe trend claims as observations about the reviewed sample rather than about the entire 2019–2024 literature.
  3. [Abstract and Section 1] There is a tension between the abstract's characterization of the review as 'comprehensive' and Section 1's disclaimer that the survey 'does not aim to be exhaustive.' If the authors intend the review to be a comprehensive methodological map, the sample must be representative in a defensible sense; if it is only a selective overview, the words 'comprehensive' and 'systematically categorized' in the abstract overstate what is delivered. This should be reconciled by either making the systematic-exhaustive methodology explicit or softening the abstract's claims to match the selective scope.
minor comments (4)
  1. [Throughout] There are numerous spacing artifacts in the text, such as 'e ffective' in the abstract and 'di fferent' in several places; a careful proofreading pass is needed.
  2. [References, Lim et al. (2019)] The reference 'Lim, G.J., Rungta, M., Davishan, A., 2019' appears to contain a typo in the third author's name (likely 'Darvishan'); please verify against the published article.
  3. [Table 1] The abbreviation CTP is listed in Table 1 but is never used in the text; conversely, the term MEDEVAC appears with a stray space in the table ('MEDEV AC'). Minor consistency check is recommended.
  4. [Section 5.2] The machine-learning subsection for search and rescue exists and includes relevant RL/pointer-network papers, but the introduction's statement excluding 'simulation in search and rescue' is not revisited in Section 5; a brief explanation of why simulation is absent (or a correction) would improve coherence.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular reasoning found: this is a scoping literature review with no fitted parameters, no predictions, and no derivation chain that reduces to its inputs.

full rationale

This paper is a narrative survey of 2019-2024 disaster emergency response planning literature organized by five application areas and three methodological lenses. It contains no mathematical derivation, no fitted model, and no empirical prediction that could be circular by construction. The introduction explicitly states that the survey is not exhaustive and that representative studies are selected from named publishers and databases, so the survey's aggregate claims are explicitly summaries of the included sample rather than results derived from a model. The few self-citations (e.g., Yin et al. 2023 and Pu et al. 2022 cited as examples of Benders decomposition in Section 2.1; Ma et al. 2022 and Allison et al. 2024 cited as examples of reinforcement learning in Section 4.2) are used only as illustrative instances of methods in the field, not as load-bearing premises that define the paper's conclusions. Even if one questioned the representativeness of the selected literature, that would be a concern about sampling and completeness, not about circularity: the paper does not define its categories in terms of its conclusions, nor does it rename a fitted input as a prediction. The stated exclusion of machine learning in facility location and simulation in search and rescue is an explicit scope decision, not an equivalence smuggled in as a result. Accordingly, no circularity step meets the evidentiary standard of exhibiting a specific reduction, and the appropriate score is 0.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

This is a review paper, so there are no fitted parameters or invented entities. The load-bearing assumptions are the choice of the five-area partition, the representativeness of the selected papers, and the completeness of the three-methodology categorization. These are domain assumptions that structure the entire survey.

assumptions (3)
  • domain assumption The five areas (evacuation, facility location, casualty transport, search and rescue, relief distribution) are the appropriate partition of disaster emergency response planning.
    The entire survey structure depends on this partition, asserted in the introduction without justification from a formal framework.
  • domain assumption The reviewed papers are representative of the 2019 to 2024 literature in the field.
    The survey's conclusions about trends rely on the representativeness of the manually selected papers, which is asserted but not demonstrated (Section 1).
  • domain assumption The three-methodology categorization (optimization, machine learning, simulation) is exhaustive and meaningful for all five areas.
    The paper structures every section by these three approaches and excludes other potential categories (e.g., pure statistical methods) without discussion.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Recent Advances in Disaster Emergency Response Planning: Integrating Optimization, Machine Learning, and Simulation." pith.science (2026). https://pith.science/paper/DIFB4HV5

@misc{pith2026250503979,
  author       = {Pith},
  title        = {Pith review of: Recent Advances in Disaster Emergency Response Planning: Integrating Optimization, Machine Learning, and Simulation},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/DIFB4HV5}},
  note         = {Machine review of arXiv:2505.03979}
}
read the original abstract

The increasing frequency and severity of natural disasters underscore the critical importance of effective disaster emergency response planning to minimize human and economic losses. This survey provides a comprehensive review of recent advancements (2019--2024) in five essential areas of disaster emergency response planning: evacuation, facility location, casualty transport, search and rescue, and relief distribution. Research in these areas is systematically categorized based on methodologies, including optimization models, machine learning, and simulation, with a focus on their individual strengths and synergies. A notable contribution of this work is its examination of the interplay between machine learning, simulation, and optimization frameworks, highlighting how these approaches can address the dynamic, uncertain, and complex nature of disaster scenarios. By identifying key research trends and challenges, this study offers valuable insights to improve the effectiveness and resilience of emergency response strategies in future disaster planning efforts.

Figures

Figures reproduced from arXiv: 2505.03979 by the authors.

Figure 1
Figure 1. Review Framework of Disaster Emergency Response Planning [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ML-MaxProp: Bridging Machine Learning and Delay-Tolerant Routing for Resilient Post-Disaster Communication

    cs.NI 2025-08 reject novelty 3.0 of 10

    ML-MaxProp embeds an XGBoost classifier into MaxProp to predict relay suitability in disaster networks, but the claimed performance gains are not backed by any presented data.

Reference graph

Works this paper leans on

103 extracted references · 78 canonical work pages · cited by 1 Pith paper

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in ":" * " " * FUNCTION f...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in ":" * " " * FUNCTION f...

  3. [3]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in ":" * " " * FUNCTION f...

  4. [4]

    , author Habib, M.A

    author Alam, M.J. , author Habib, M.A. , author Husk, D. , year 2022 . title Evacuation planning for persons with mobility needs: A combined optimization and traffic microsimulation modelling approach . journal International Journal of Disaster Risk Reduction volume 80 , pages 103164

    2022

  5. [5]

    , author Li, Z

    author Allison, J. , author Li, Z. , author Ma, C. , author Zhang, Y. , author Wang, X.B. , year 2024 . title Performance evaluation of reinforcement learning-based adaptive signal control deployment in urban network . journal IFAC-PapersOnLine volume 58 , pages 120--125

    2024

  6. [6]

    , author Green III, W.G

    author Altay, N. , author Green III, W.G. , year 2006 . title Or/ms research in disaster operations management . journal European journal of operational research volume 175 , pages 475--493

    2006

  7. [7]

    O zener, O. \

    author Avishan, F. , author Elyasi, M. , author Yan ko g lu, \.I . , author Ekici, A. , author \"O zener, O. \"O . , year 2023 . title Humanitarian relief distribution problem: an adjustable robust optimization approach . journal Transportation science volume 57 , pages 1096--1114

    2023

  8. [8]

    , author Johansson, K.H

    author Bagloee, S.A. , author Johansson, K.H. , author Asadi, M. , year 2019 . title A hybrid machine-learning and optimization method for contraflow design in post-disaster cases and traffic management scenarios . journal Expert Systems with Applications volume 124 , pages 67--81

    2019

Show all 103 references
  1. [9]

    , author Yan ko g lu, \.I

    author Balcik, B. , author Yan ko g lu, \.I . , year 2020 . title A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty . journal European Journal of Operational Research volume 282 , pages 40--57

    2020

  2. [10]

    , author Yaman, H

    author Bayram, V. , author Yaman, H. , year 2024 . title A joint demand and supply management approach to large scale urban evacuation planning: Evacuate or shelter-in-place, staging and dynamic resource allocation . journal European Journal of Operational Research volume 313 ...

    2024

  3. [11]

    , author Pham, H

    author Bello, I. , author Pham, H. , author Le, Q.V. , author Norouzi, M. , author Bengio, S. , year 2016 . title Neural combinatorial optimization with reinforcement learning . journal arXiv preprint arXiv:1611.09940

    2016 arXiv

  4. [12]

    , author Song, Y

    author Bhattarai, S. , author Song, Y. , year 2024 . title Multistage stochastic programming for integrated network optimization in hurricane relief logistics and evacuation planning . journal Networks

    2024

  5. [13]

    , author Leiras, A

    author Bravo, R.Z.B. , author Leiras, A. , author Cyrino Oliveira, F.L. , year 2019 . title The use of uavs in humanitarian relief: An application of pomdp-based methodology for finding victims . journal Production and Operations Management volume 28 , pages 421--440

    2019

  6. [14]

    , author Nie, X

    author Caunhye, A.M. , author Nie, X. , author Pokharel, S. , year 2012 . title Optimization models in emergency logistics: A literature review . journal Socio-economic planning sciences volume 46 , pages 4--13

    2012

  7. [15]

    , author Chen, T.L

    author Chang, K.H. , author Chen, T.L. , author Yang, F.H. , author Chang, T.Y. , year 2023 . title Simulation optimization for stochastic casualty collection point location and resource allocation problem in a mass casualty incident . journal European Journal of Operational R...

    2023

  8. [16]

    , author Sun, Y

    author Chen, S. , author Sun, Y. , author Zhao, T. , author Jia, M. , author Tang, T. , year 2024 . title Data-driven modeling of hurricane evacuee’s individual decision-making for enhanced hurricane evacuation planning: Florida case study in the covid-19 pandemic . journal Na...

    2024

  9. [17]

    , author Chiang, W.C

    author Chou, C.C. , author Chiang, W.C. , author Chen, A.Y. , year 2022 . title Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays . journal Transportation research part E: logistics and transporta...

    2022

  10. [18]

    , author \"U ster, H

    author Dalal, J. , author \"U ster, H. , year 2021 . title Robust emergency relief supply planning for foreseen disasters under evacuation-side uncertainty . journal Transportation science volume 55 , pages 791--813

    2021

  11. [19]

    , author Lim, G.J

    author Darvishan, A. , author Lim, G.J. , year 2021 . title Dynamic network flow optimization for real-time evacuation reroute planning under multiple road disruptions . journal Reliability Engineering & System Safety volume 214 , pages 107644

    2021

  12. [20]

    , author Sabouhi, F

    author Desi-Nezhad, Z. , author Sabouhi, F. , author Sadrabadi, M.H.D. , year 2022 . title An optimization approach for disaster relief network design under uncertainty and disruption with sustainability considerations . journal RAIRO-Operations Research volume 56 , pages 751--768

    2022

  13. [21]

    , author Kim, G

    author Douris, J. , author Kim, G. , year 2021 . title The atlas of mortality and economic losses from weather, climate and water extremes (1970-2019)

    2021

  14. [22]

    , author Albert, L.A

    author DuBois, E. , author Albert, L.A. , year 2021 . title Dispatching policies during prolonged mass casualty incidents . journal Journal of the Operational Research Society volume 73 , pages 2536--2550

    2021

  15. [23]

    , author Guerrero, W.J

    author Espejo-D \' az, J.A. , author Guerrero, W.J. , year 2021 . title A multiagent approach to solving the dynamic postdisaster relief distribution problem . journal Operations Management Research volume 14 , pages 177--193

    2021

  16. [24]

    , author Scaparra, M.P

    author Esposito Amideo, A. , author Scaparra, M.P. , author Sforza, A. , author Sterle, C. , year 2021 . title An integrated user-system approach for shelter location and evacuation routing . journal Networks volume 78 , pages 46--68

    2021

  17. [25]

    , author Chang, X

    author Fan, J. , author Chang, X. , author Mi s i \'c , J. , author Mi s i \'c , V.B. , author Kang, H. , year 2022 . title Dhl: Deep reinforcement learning-based approach for emergency supply distribution in humanitarian logistics . journal Peer-to-Peer Networking and Applica...

    2022

  18. [26]

    , author Evans, B

    author Fathianpour, A. , author Evans, B. , author Jelodar, M.B. , author Wilkinson, S. , year 2023 . title Tsunami evacuation modelling via micro-simulation model . journal Progress in disaster science volume 17 , pages 100277

    2023

  19. [27]

    , author Liu, T

    author Feng, Y. , author Liu, T. , author Hu, Z. , author Wang, D. , author Cheng, T. , author Yin, Y. , year 2021 . title Casualty transport scheduling considering survival probability and injury classification . journal Computers & Industrial Engineering volume 161 , pages 107655

    2021

  20. [28]

    , author Batta, R

    author Galindo, G. , author Batta, R. , year 2013 . title Review of recent developments in or/ms research in disaster operations management . journal European journal of operational research volume 230 , pages 201--211

    2013

  21. [29]

    , author Fernandes, H.L

    author Gama, R. , author Fernandes, H.L. , year 2021 . title A reinforcement learning approach to the orienteering problem with time windows . journal Computers & Operations Research volume 133 , pages 105357

    2021

  22. [30]

    , author Meyer, A

    author Glock, K. , author Meyer, A. , year 2020 . title Mission planning for emergency rapid mapping with drones . journal Transportation science volume 54 , pages 534--560

    2020

  23. [31]

    , author Van Hentenryck, P

    author Hafiz Hasan, M. , author Van Hentenryck, P. , year 2021 . title Large-scale zone-based evacuation planning—part i: Models and algorithms . journal Networks volume 77 , pages 127--145

    2021

  24. [32]

    , author Roebber, P

    author Harris, A. , author Roebber, P. , author Morss, R. , year 2022 . title An agent-based modeling framework for examining the dynamics of the hurricane-forecast-evacuation system . journal International journal of disaster risk reduction volume 67 , pages 102669

    2022

  25. [33]

    , author Van Hentenryck, P

    author Hasan, M.H. , author Van Hentenryck, P. , year 2021 . title Large-scale zone-based evacuation planning, part ii: Macroscopic and microscopic evaluations . journal Networks volume 77 , pages 341--358

    2021

  26. [34]

    , author Ameli, M

    author Idoudi, H. , author Ameli, M. , author Van Phu, C.N. , author Zargayouna, M. , author Rachedi, A. , year 2022 . title An agent-based dynamic framework for population evacuation management . journal IEEE Access volume 10 , pages 88606--88620

    2022

  27. [35]

    , author Rafique, R.A

    author Jat, M.N. , author Rafique, R.A. , year 2020 . title Mass-casualty distribution for emergency healthcare: a simulation analysis . journal International Journal of Disaster Risk Science volume 11 , pages 364--377

    2020

  28. [36]

    , author Robbins, M.J

    author Jenkins, P.R. , author Robbins, M.J. , author Lunday, B.J. , year 2021 a. title Approximate dynamic programming for military medical evacuation dispatching policies . journal INFORMS Journal on Computing volume 33 , pages 2--26

    2021

  29. [37]

    , author Robbins, M.J

    author Jenkins, P.R. , author Robbins, M.J. , author Lunday, B.J. , year 2021 b. title Approximate dynamic programming for the military aeromedical evacuation dispatching, preemption-rerouting, and redeployment problem . journal European Journal of Operational Research volume ...

    2021

  30. [38]

    , author Ng, K.K

    author Jin, Z. , author Ng, K.K. , author Zhang, C. , author Liu, W. , author Zhang, F. , author Xu, G. , year 2024 . title A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem . journal Transportation Research Part E...

    2024

  31. [39]

    , author Manzour, H

    author Karabuk, S. , author Manzour, H. , year 2019 . title A multi-stage stochastic program for evacuation management under tornado track uncertainty . journal Transportation research part E: logistics and transportation review volume 124 , pages 128--151

    2019

  32. [40]

    , author Kioskli, K

    author Karampotsis, E. , author Kioskli, K. , author Tsirimpa, A. , author Dounias, G. , author Polydoropoulou, A. , year 2024 . title Understanding evacuation behavior for effective disaster preparedness: a hybrid machine learning approach . journal Natural Hazards , pages 1--39

    2024

  33. [41]

    , author Samany, N.N

    author Keykhaei, M. , author Samany, N.N. , author Jelokhani-Niaraki, M. , author Zlatanova, S. , year 2024 . title Multi-agent-based human cognition simulation of situation-aware earthquake emergency evacuation . journal International Journal of Disaster Risk Reduction volume...

    2024

  34. [42]

    , author Tavana, M

    author Khalili-Damghani, K. , author Tavana, M. , author Ghasemi, P. , year 2022 . title A stochastic bi-objective simulation--optimization model for cascade disaster location-allocation-distribution problems . journal Annals of operations research volume 309 , pages 103--141

    2022

  35. [43]

    , author Kaviari, F

    author Kim, K. , author Kaviari, F. , author Pant, P. , author Yamashita, E. , year 2022 . title An agent-based model of short-notice tsunami evacuation in waikiki, hawaii . journal Transportation research part D: transport and environment volume 105 , pages 103239

    2022

  36. [44]

    , author Ahn, J

    author Lee, D.H. , author Ahn, J. , year 2024 . title Multi-start team orienteering problem for uas mission re-planning with data-efficient deep reinforcement learning . journal Applied Intelligence volume 54 , pages 4467--4489

    2024

  37. [45]

    , author Lee, T

    author Lee, H.R. , author Lee, T. , year 2021 . title Multi-agent reinforcement learning algorithm to solve a partially-observable multi-agent problem in disaster response . journal European Journal of Operational Research volume 291 , pages 296--308

    2021

  38. [46]

    , author Lee, Y.H

    author Lee, S. , author Lee, Y.H. , year 2020 . title Improving emergency department efficiency by patient scheduling using deep reinforcement learning . journal Healthcare volume 8 , pages 77

    2020

  39. [47]

    , author Zhang, J

    author Li, Y. , author Zhang, J. , author Yu, G. , year 2020 . title A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters . journal Transportation Research Part E: Logistics and ...

    2020

  40. [48]

    , author Yu, H

    author Li, Z. , author Yu, H. , author Chen, X. , author Zhang, G. , author Ma, D. , year 2019 . title Tsunami-induced traffic evacuation strategy optimization . journal Transportation research part D: transport and environment volume 77 , pages 535--559

    2019

  41. [49]

    , author Zhang, Y

    author Li, Z. , author Zhang, Y. , author Wang, B. , et al., year 2023 . title Prediction of port recovery time after a severe storm project

    2023

  42. [50]

    , author Rungta, M

    author Lim, G.J. , author Rungta, M. , author Davishan, A. , year 2019 . title A robust chance constraint programming approach for evacuation planning under uncertain demand distribution . journal IISE Transactions volume 51 , pages 589--604

    2019

  43. [51]

    , author Sheu, J.B

    author Liu, B. , author Sheu, J.B. , author Zhao, X. , author Chen, Y. , author Zhang, W. , year 2020 . title Decision making on post-disaster rescue routing problems from the rescue efficiency perspective . journal European Journal of Operational Research volume 286 , pages 321--335

    2020

  44. [52]

    , author Cui, N

    author Liu, Y. , author Cui, N. , author Zhang, J. , year 2019 . title Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service . journal Transportation research part E: logistics and transportation review volume 12...

    2019

  45. [53]

    , author Wang, B

    author Ma, C. , author Wang, B. , author Li, Z. , author Mahmoudzadeh, A. , author Zhang, Y. , year 2022 . title Lyapunov function consistent adaptive network signal control with back pressure and reinforcement learning . journal arXiv preprint arXiv:2210.02612

    2022 arXiv

  46. [54]

    , author Gelareh, S

    author Monemi, R.N. , author Gelareh, S. , author Nagih, A. , author Maculan, N. , author Danach, K. , year 2021 . title Multi-period hub location problem with serial demands: A case study of humanitarian aids distribution in lebanon . journal Transportation Research Part E: L...

    2021

  47. [55]

    , author Leus, R

    author Morandi, N. , author Leus, R. , author Yaman, H. , year 2024 . title The orienteering problem with drones . journal Transportation Science volume 58 , pages 240--256

    2024

  48. [56]

    , author Batta, R

    author Moskal, M.D. , author Batta, R. , year 2019 . title Adaptive unmanned aerial vehicle surveillance using a prize-collecting vertex routing model . journal Military Operations Research volume 24 , pages 5--22

    2019

  49. [57]

    , author Dasdemir, E

    author Moskal, M.D. , author Dasdemir, E. , author Batta, R. , year 2023 . title Unmanned aerial vehicle information collection missions with uncertain characteristics . journal INFORMS Journal on Computing volume 35 , pages 120--137

    2023

  50. [58]

    , author Wang, H

    author Mostafizi, A. , author Wang, H. , author Cox, D. , author Dong, S. , year 2019 . title An agent-based vertical evacuation model for a near-field tsunami: Choice behavior, logical shelter locations, and life safety . journal International journal of disaster risk reducti...

    2019

  51. [59]

    , author Jia, H

    author Moug, K. , author Jia, H. , author Shen, S. , year 2023 . title A shared-mobility-based framework for evacuation planning and operations under forecast uncertainty . journal IISE Transactions volume 55 , pages 971--984

    2023

  52. [60]

    , author Banerjee, A

    author Na, H.S. , author Banerjee, A. , year 2019 . title Agent-based discrete-event simulation model for no-notice natural disaster evacuation planning . journal Computers & Industrial Engineering volume 129 , pages 44--55

    2019

  53. [61]

    title Billion-dollar weather and climate disasters

    author National Centers for Environmental Information , year 2024 . title Billion-dollar weather and climate disasters . howpublished https://www.ncei.noaa.gov/access/billions/ . note Accessed: December 18, 2024

    2024

  54. [62]

    , author Zhai, C.H

    author Pei, S.S. , author Zhai, C.H. , author Wen, W.P. , author Yu, P. , author Wang, Z.Q. , year 2023 . title A dynamic patients dispatch and treatment model for resilience evaluation of interdependent transportation-healthcare system . journal Journal of Earthquake Engineer...

    2023

  55. [63]

    , author Golden, B

    author Poikonen, S. , author Golden, B. , year 2020 . title The mothership and drone routing problem . journal INFORMS Journal on Computing volume 32 , pages 249--262

    2020

  56. [64]

    , author Yin, J

    author Pu, F. , author Yin, J. , author Wang, Y. , author Su, S. , author Yang, L. , author Tang, T. , year 2022 . title Rolling stock allocation and timetabling for urban rail transit network with multiple depots . journal Transportation Research Record volume 2676 , pages 422--435

    2022

  57. [65]

    , author Hasan, S

    author Rahman, R. , author Hasan, S. , year 2023 . title A deep learning approach for network-wide dynamic traffic prediction during hurricane evacuation . journal Transportation research part C: emerging technologies volume 152 , pages 104126

    2023

  58. [66]

    , author Nozick, L.K

    author Rambha, T. , author Nozick, L.K. , author Davidson, R. , author Yi, W. , author Yang, K. , year 2021 . title A stochastic optimization model for staged hospital evacuation during hurricanes . journal Transportation research part E: logistics and transportation review vo...

    2021

  59. [67]

    , author Schryen, G

    author Rauchecker, G. , author Schryen, G. , year 2019 . title An exact branch-and-price algorithm for scheduling rescue units during disaster response . journal European Journal of Operational Research volume 272 , pages 352--363

    2019

  60. [68]

    , author Jenkins, P.R

    author Robbins, M.J. , author Jenkins, P.R. , author Bastian, N.D. , author Lunday, B.J. , year 2020 . title Approximate dynamic programming for the aeromedical evacuation dispatching problem: Value function approximation utilizing multiple level aggregation . journal Omega vo...

    2020

  61. [69]

    , author Jenkins, P.R

    author Rodriguez, C.A. , author Jenkins, P.R. , author Robbins, M.J. , year 2023 . title Solving the joint military medical evacuation problem via a random forest approximate dynamic programming approach . journal Expert Systems with Applications volume 221 , pages 119751

    2023

  62. [70]

    , author Seifi, A

    author Sakiani, R. , author Seifi, A. , author Khorshiddoust, R.R. , year 2020 . title Inventory routing and dynamic redistribution of relief goods in post-disaster operations . journal Computers & Industrial Engineering volume 140 , pages 106219

    2020

  63. [71]

    , author Daskin, M.S

    author Sanci, E. , author Daskin, M.S. , year 2021 . title An integer l-shaped algorithm for the integrated location and network restoration problem in disaster relief . journal Transportation Research Part B: Methodological volume 145 , pages 152--184

    2021

  64. [72]

    , author Tavakkoli-Moghaddam, R

    author Seraji, H. , author Tavakkoli-Moghaddam, R. , author Asian, S. , author Kaur, H. , year 2022 . title An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty . journal Annals of Operations Rese...

    2022

  65. [73]

    , author Liu, N

    author Shi, Y. , author Liu, N. , author Wan, G. , year 2024 . title Treatment planning for victims with heterogeneous time sensitivities in mass casualty incidents . journal Operations Research volume 72 , pages 1400--1420

    2024

  66. [74]

    , author Lee, T

    author Shin, K. , author Lee, T. , year 2020 . title Emergency medical service resource allocation in a mass casualty incident by integrating patient prioritization and hospital selection problems . journal IISE Transactions volume 52 , pages 1141--1155

    2020

  67. [75]

    , author Akbari, V

    author Shiri, D. , author Akbari, V. , author Hassanzadeh, A. , year 2024 a. title The capacitated team orienteering problem: An online optimization framework with predictions of unknown accuracy . journal Transportation Research Part B: Methodological volume 185 , pages 102984

    2024

  68. [76]

    , author Akbari, V

    author Shiri, D. , author Akbari, V. , author Salman, F.S. , year 2020 . title Online routing and scheduling of search-and-rescue teams . journal OR Spectrum volume 42 , pages 755--784

    2020

  69. [77]

    , author Akbari, V

    author Shiri, D. , author Akbari, V. , author Salman, F.S. , year 2024 b. title Online algorithms for ambulance routing in disaster response with time-varying victim conditions . journal OR Spectrum , pages 1--35

    2024

  70. [78]

    , author Song, Y

    author Siddig, M. , author Song, Y. , year 2024 . title Multistage stochastic programming with a random number of stages: Applications in hurricane disaster relief logistics planning . journal European Journal of Operational Research

    2024

  71. [79]

    , author Sinimole, K

    author Sreejith, R. , author Sinimole, K. , year 2022 . title Modelling evacuation preparation time prior to floods: A machine learning approach . journal Sustainable Cities and Society volume 87 , pages 104257

    2022

  72. [80]

    , author Li, J

    author Sun, H. , author Li, J. , author Wang, T. , author Xue, Y. , year 2022 . title A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions . journal Transportation research part E: logistics and transportati...

    2022

  73. [81]

    , author Huang, S.K

    author Sun, Y. , author Huang, S.K. , author Zhao, X. , year 2024 . title Predicting hurricane evacuation decisions with interpretable machine learning methods . journal International Journal of Disaster Risk Science volume 15 , pages 134--148

    2024

  74. [82]

    , author Nistor, I

    author Takabatake, T. , author Nistor, I. , author St-Germain, P. , year 2020 . title Tsunami evacuation simulation for the district of tofino, vancouver island, canada . journal International Journal of Disaster Risk Reduction volume 48 , pages 101573

    2020

  75. [83]

    , author Mes, M

    author Van Steenbergen, R. , author Mes, M. , author Van Heeswijk, W. , year 2023 . title Reinforcement learning for humanitarian relief distribution with trucks and uavs under travel time uncertainty . journal Transportation Research Part C: Emerging Technologies volume 157 ,...

    2023

  76. [84]

    , author Xu, G

    author Wan, P. , author Xu, G. , author Chen, J. , author Zhou, Y. , year 2024 . title Deep reinforcement learning enabled multi-uav scheduling for disaster data collection with time-varying value . journal IEEE Transactions on Intelligent Transportation Systems

    2024

  77. [85]

    , author Deng, W

    author Wang, B. , author Deng, W. , author Tan, Z. , author Zhang, B. , author Chen, F. , year 2024 a. title A two-stage stochastic optimization for disaster rescue resource distribution considering multiple disasters . journal Engineering Optimization volume 56 , pages 1--17

    2024

  78. [86]

    , author Liu, W

    author Wang, R. , author Liu, W. , author Li, K. , author Zhang, T. , author Wang, L. , author Xu, X. , year 2024 b. title Solving orienteering problems by hybridizing evolutionary algorithm and deep reinforcement learning . journal IEEE Transactions on Artificial Intelligence

    2024

  79. [87]

    , author Chen, X

    author Wang, Y. , author Chen, X. , author Wang, L. , year 2023 . title Deep reinforcement learning-based rescue resource distribution scheduling of storm surge inundation emergency logistics . journal IEEE Transactions on Industrial Informatics volume 19 , pages 10004--10013

    2023

  80. [88]

    , author Jacobs, P

    author Wilcox, C. , author Jacobs, P. , year 2024 . title Hurricane-battered researchers assess damage . journal Science (New York, NY) volume 386 , pages 367

    2024

  81. [89]

    , author Sun, Z

    author Xia, H. , author Sun, Z. , author Wang, Y. , author Zhang, J.Z. , author Kamal, M.M. , author Jasimuddin, S.M. , author Islam, N. , year 2023 . title Emergency medical supplies scheduling during public health emergencies: algorithm design based on ai techniques . journa...

    2023

  82. [90]

    , author Zhang, K

    author Yang, Y. , author Zhang, K. , author Song, H. , author Liu, D. , year 2021 . title Machine learning-enabled adaptive air traffic recommendation system for disaster evacuation , in: booktitle 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC) , organization I...

    2021

  83. [91]

    , author Pu, F

    author Yin, J. , author Pu, F. , author Yang, L. , author D’ariano, A. , author Wang, Z. , year 2023 . title Integrated optimization of rolling stock allocation and train timetables for urban rail transit networks: A benders decomposition approach . journal Transportation Rese...

    2023

  84. [92]

    , author Xu, X

    author Yin, Y. , author Xu, X. , author Wang, D. , author Yu, Y. , author Cheng, T. , year 2024 . title Two-stage recoverable robust optimization for an integrated location--allocation and evacuation planning problem . journal Transportation research part B: methodological vol...

    2024

  85. [93]

    , year 2024

    author Yoon, J. , year 2024 . title Wildfires prompt evacuations in texas and oklahoma. journal The New York Times

    2024

  86. [94]

    , author Albert, L.A

    author Yoon, S. , author Albert, L.A. , year 2021 . title Dynamic dispatch policies for emergency response with multiple types of vehicles . journal Transportation Research Part E: Logistics and Transportation Review volume 152 , pages 102405

    2021

  87. [95]

    , author Zhang, C

    author Yu, L. , author Zhang, C. , author Jiang, J. , author Yang, H. , author Shang, H. , year 2021 . title Reinforcement learning approach for resource allocation in humanitarian logistics . journal Expert Systems with Applications volume 173 , pages 114663

    2021

  88. [96]

    , author Adulyasak, Y

    author Yu, Q. , author Adulyasak, Y. , author Rousseau, L.M. , author Zhu, N. , author Ma, S. , year 2022 a. title Team orienteering with time-varying profit . journal INFORMS Journal on Computing volume 34 , pages 262--280

    2022

  89. [97]

    , author Cheng, C

    author Yu, Q. , author Cheng, C. , author Zhu, N. , year 2022 b. title Robust team orienteering problem with decreasing profits . journal INFORMS Journal on Computing volume 34 , pages 3215--3233

    2022

  90. [98]

    , author Zhu, N

    author Zhang, G. , author Zhu, N. , author Ma, S. , author Xia, J. , year 2021 . title Humanitarian relief network assessment using collaborative truck-and-drone system . journal Transportation Research Part E: Logistics and Transportation Review volume 152 , pages 102417

    2021

  91. [99]

    , author Zhang, Y

    author Zhang, M. , author Zhang, Y. , author Jiao, Z. , author Wang, J. , year 2023 . title Improving relief operations via optimizing shelter location with uncertain covariates . journal Transportation Research Part E: Logistics and Transportation Review volume 176 , pages 103181

    2023

  92. [100]

    , author Ji, K

    author Zhao, X. , author Ji, K. , author Xu, P. , author Qian, W.w. , author Ren, G. , author Shan, X.n. , year 2020 . title A round-trip bus evacuation model with scheduling and routing planning . journal Transportation Research Part A: Policy and Practice volume 137 , pages 285--300

    2020

  93. [101]

    , author Du, Y.C

    author Zheng, Y.J. , author Du, Y.C. , author Sheng, W.G. , author Ling, H.F. , year 2019 . title Collaborative human--uav search and rescue for missing tourists in nature reserves . journal INFORMS Journal on Applied Analytics volume 49 , pages 371--383

    2019

  94. [102]

    , author Cheng, R

    author Zhong, S. , author Cheng, R. , author Jiang, Y. , author Wang, Z. , author Larsen, A. , author Nielsen, O.A. , year 2020 . title Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand . journal Transportation Research P...

    2020

  95. [103]

    , author Li, Z

    author Zhou, Y. , author Li, Z. , author Meng, Y. , author Li, Z. , author Zhong, M. , year 2021 . title Analyzing spatio-temporal impacts of extreme rainfall events on metro ridership characteristics . journal Physica A: Statistical Mechanics and its Applications volume 577 ,...

    2021

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.