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Joseph Chow, A. Regan (2011)
Resource Location and Relocation Models with Rolling Horizon Forecasting for Wildland Fire PlanningINFOR: Information Systems and Operational Research, 49
J. Artalejo (2013)
Editorial - MCQT'10: computational methods and applications in queueing theoryAnn. Oper. Res., 202
Constantine Toregas, R. Swain, C. Revelle, Lawrence Bergman (1971)
The Location of Emergency Service FacilitiesOper. Res., 19
NtaimoLewis, ArrublaJulián Gallego, StriplingCurt, YoungJoshua, SpencerThomas (2012)
A stochastic programming standard response model for wildfire initial attack planningCanadian Journal of Forest Research, 42
M. Dimopoulou, I. Giannikos (2004)
Towards an integrated framework for forest fire controlEur. J. Oper. Res., 152
E. Mitsakis, I. Stamos, M. Diakakis, J. Grau (2014)
Impacts of high-intensity storms on urban transportation: applying traffic flow control methodologies for quantifying the effectsInternational Journal of Environmental Science and Technology, 11
R. Haight (2007)
Deploying Wildland Fire Suppression Resources with a Scenario-Based Standard Response ModelINFOR: Information Systems and Operational Research, 45
E. Mitsakis, I. Stamos, A. Papanikolaou, G. Aifadopoulou, H. Kontoes (2013)
Assessment of extreme weather events on transport networks: case study of the 2007 wildfires in PeloponnesusNatural Hazards, 72
Hao Lei, R. Cheu, R. Aldouri (2009)
Optimal Allocation of Emergency Response Service Units to Cover Critical Infrastructures with Time-Dependent Service Demand and Travel TimeTransportation Research Record, 2137
M. Garey, D. Johnson
Computers and Intractability: A Guide to the Theory of NP‐Completeness, ISBN 0‐7167‐1045‐5
Yohan Lee, J. Fried, H. Albers, R. Haight (2013)
Deploying initial attack resources for wildfire suppression: spatial coordination, budget constraints, and capacity constraintsCanadian Journal of Forest Research, 43
Kazi Islam, D. Martell (1998)
Performance of initial attack airtanker systems with interacting bases and variable initial attack rangesCanadian Journal of Forest Research, 28
European Forest Fire Information System
Forest fires in Europe, Report No 8
Ceyhun Araz, Hasan Selim, I. Ozkarahan (2007)
A fuzzy multi-objective covering-based vehicle location model for emergency servicesComput. Oper. Res., 34
J. Bookbinder, D. Martell (1979)
Time-Dependent Queueing Approach to Helicopter Allocation for Forest Fire Initial-AttackInfor, 17
European Space Agency
Greece suffers more fires in 2007 than in last decade, satellites reveal
F.E. Greulich, W.G. O'Regan
Allocation Model for Air Tanker Initial Attack in Firefighting
R. Benveniste (1985)
Solving the Combined Zoning and Location Problem for Several Emergency UnitsJournal of the Operational Research Society, 36
David Johnson (1982)
The NP-Completeness Column: An Ongoing GuideJ. Algorithms, 4
M. Dimopoulou, I. Giannikos (2001)
Spatial Optimization of Resources Deployment for Forest-Fire ManagementInternational Transactions in Operational Research, 8
R. Church, C. Revelle (1974)
The maximal covering location problemPapers of the Regional Science Association, 32
Georgia Ayfadopoulou, I. Stamos, E. Mitsakis, Josep Grau (2012)
Dynamic Traffic Assignment Based Evacuation Planning for CBD AreasProcedia - Social and Behavioral Sciences, 48
J. Minas, J. Hearne, D. Martell (2013)
An integrated optimization model for fuel management and fire suppression preparedness planningAnnals of Operations Research, 232
M. Hodgson, R. Newstead (1978)
Location-allocation models for one-strike initial attack of forest fires by airtankersCanadian Journal of Forest Research, 8
E. Mitsakis, I. Stamos, Josep Grau, Evangelia Chrysochoou, Panagiotis Iordanopoulos, G. Aifadopoulou (2013)
Urban Mobility Indicators for ThessalonikiJournal of Traffic and Logistics Engineering, 1
C. Melolidakis (1993)
Designing the allocation of emergency units by using the Shapley-Shubik power index: a case studyMathematical and Computer Modelling, 18
J. MacLellan, D. Martell (1996)
Basing Airtankers for Forest Fire Control in OntarioOper. Res., 44
N. Geroliminis, K. Kepaptsoglou, M. Karlaftis (2011)
A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban networkEur. J. Oper. Res., 210
Purpose – The purpose of this paper is to present and apply a methodology that optimally assigns emergency response services (ERS) stations in Peloponnesus, Greece that was severely hit by wildfires in 2007, in an effort to describe the actual emergency response in this disaster and identify disaster management possibilities that can arise from the optimal allocation of the existing fire stations. Design/methodology/approach – The methodology concerns the development of an objective function that aims to minimize maximum and average response times of ERS stations and the evaluation of developed scenarios. Simulated annealing is used for the minimization of the objective function, providing near‐optimal solutions with low computation times for medium‐scale networks. Findings – The findings concern the comparison of average and maximum response times of ERS stations to hearths of fire, based on their actual and optimal allocation. They reveal an overall reduction in the average and maximum response time by 20 and 30 percent, respectively, for the entire region, while there is a reduction of 15 and 35 percent in the average and maximum response time for the locations affected by the 2007 wildfires. Research limitations/implications – The methodology is formulated as a facility location problem with unitary demand and unlimited capacity in the stations, which means that the allocation does not take into account simultaneous events. Originality/value – The paper fulfills an identified need to apply innovative research solutions to actual case studies in order to identify existing gaps and future disaster management possibilities.
Disaster Prevention and Management – Emerald Publishing
Published: Jul 29, 2014
Keywords: Greece; Disasters management; Emergency response services; Optimal allocation of ERS stations; Response times minimization
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