ОПТИМАЛЬНАЯ МАРШРУТИЗАЦИЯ ВОЗДУШНЫХ СУДОВ И МАШИН СКОРОЙ ПОМОЩИ В ЛОГИСТИКЕ ПРИ СТИХИЙНЫХ БЕДСТВИЯХ

One of the most vital aspects of emergency management studies is the development and examination of post-disaster search and rescue activities and treatment facilities. One of such issues to be considered while performing these operations is to reach the disaster victims within minimum time and to plan disaster logistics in the most efficient manner possible. In this study, the problem of planning debris scanning activities with Unmanned Aerial Vehicles after an earthquake and transporting the injured people to the hospitals by ambulances within minimum time was discussed, and mathematical models were developed to solve the problem. The ambulance routing problem and the mathematical model to be used in the solution to the problem are discussed for the first time in the literature. The developed model was tested on the problem sets created by taking into account the data of the province under investigation.Одним из наиболее важных аспектов исследований по управлению рисками и чрезвычайными ситуациями является разработка и изучение поисково-спасательных мероприятий и очистных сооружений после стихийных бедствий. Одним из вопросов, которые необходимо учитывать при выполнении этих операций, является обеспечение доступа к жертвам стихийных бедствий в минимальные сроки и планирование логистики в случае стихийных бедствий наиболее эффективным способом. В данном исследовании рассматривается проблема планирования работ по спасению с помощью беспилотных летательных аппаратов после землетрясения и транспортировки пострадавших людей в больницы на машинах скорой помощи за минимальное время. Для решения этой проблемы были разработаны и предложены математические модели. Впервые рассматривается задача маршрутизации скорой помощи и математическая модель, которая будет использоваться для решения этой задачи. Разработанная модель была протестирована на множествах задач, созданных с учетом реальных данных исследуемой провинции Турции

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation

Pre-positioning of relief items under road/facility vulnerability with concurrent restoration and relief transportation

Planning for response to sudden-onset disasters such as earthquakes, hurricanes, or floods needs to take into account the inherent uncertainties regarding the disaster and its impacts on the affected people as well as the logistics network. This article focuses on the design of a multi-echelon humanitarian response network, where the pre-disaster decisions of warehouse location and item pre-positioning are subject to uncertainties in relief item demand and vulnerability of roads and facilities following the disaster. Once the disaster strikes, relief transportation is accompanied by simultaneous repair of blocked roads, which delays the transportation process, but gradually increases the connectivity of the network at the same time. A two-stage stochastic program is formulated to model this system and a Sample Average Approximation (SAA) scheme is proposed for its heuristic solution. To enhance the efficiency of the SAA algorithm, we introduce a number of valid inequalities and bounds on the objective value. Computational experiments on a potential earthquake scenario in Istanbul, Turkey show that the SAA scheme is able to provide an accurate approximation of the objective function in reasonable time, and can help drive policy-based implications that may be applicable in preparation for similar potential disaster

Using simulation gaming to validate a mathematical modeling platform for resource allocation in disasters

The extraordinary conditions of a disaster require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning In an attempt to reduce the partner proliferation problem a framework called PREDIS (PREdictive model for DISaster response partner selection) is put forward to configure the humanitarian network within early hours after disaster strike when the information is scarce To verify this model a simulation game is designed using two sets of real decision makers (experts and non-experts) in the disaster Haiyan scenario The result shows that using the PREDIS framework 100% of the experts could make the same decisions less than six hours comparing to 72 hours Also between 71% and 86% of the times experts and non-experts decide similarly using the PREDIS framewor

Designing a Relief Distribution Network under Uncertain Situation: Preparedness in Responding to Disaster

None can predict a disaster precisely: where, when, and how big a disaster will strike one area. This situation leads to uncertainty in such as required demand and supply availabilities. To an area that has been identified threatening by a natural hazard, a possible disaster scenario may compile. Since time is vital in disaster response operations, developing strategies to speed up emergency response is necessitated. This study is aimed to develop a stochastic model for a location-allocation problem in responding to a forecasted disaster. Our stochastic approach recommends a number and locations of local distribution centers (LDCs) that are required to be set up in the initial stage of the response phase and a number of relief items that will be dispatched to survivors in the affected areas through the proposed relief network. A mixed delivery strategy is applied in a 3-tier of a relief distribution network encompassing warehouses, LDCs, and shelters. This strategy provides the affected people in some of the shelters to receive relief items directly from nearby warehouses, while the remaining shelters will get supplies indirectly through the opened LDCs. Comparing to the indirect strategy that shelters are permitted to receive aid goods only through LDCs, the proposed mixed delivery strategy provides more efficient and effective relief distribution. The probable tsunami in West Sumatra, Indonesia, known as Mentawai Megathrust, is employed to illustrate the developed model. The model will be beneficial for disaster managers to improve the performance of a disaster relief operation

Characterizing Logistics Operations Within a Federal Staging Area for Hurricane Response: A Qualitative Analysis of Federal, State and Local Perspectives

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete knowledge of infrastructure status poses serious critical transportation risks such as delivery delays in disaster relief distribution. This research reveals both similarities and differences in logistical decision-making among these organization types and emphasizes the need for improved information sharing and coordination among emergency response organizations. The findings of this research are expected to guide future initiatives aimed at disaster relief routing thereby enhancing emergency response capabilities and outcomes

Characterizing Logistics Operations Within a Federal Staging Area for Hurricane Response: A Qualitative Analysis of Federal, State and Local Perspectives

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete knowledge of infrastructure status poses serious critical transportation risks such as delivery delays in disaster relief distribution. This research reveals both similarities and differences in logistical decision-making among these organization types and emphasizes the need for improved information sharing and coordination among emergency response organizations. The findings of this research are expected to guide future initiatives aimed at disaster relief routing thereby enhancing emergency response capabilities and outcomes

Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty : A System Design Approach

With respect to copyright, all the papers were excluded from the dissertation.Disasters threaten society with widespread destruction of infrastructure and livelihood. For their survival, affected inhabitants depend on immediate humanitarian assistance from diverse organizations. During quick responses, humanitarian decision- makers (HDMs) act rapidly to distribute necessary relief goods, despite the deep, prevailing uncertainty that arises from scarce, conflicting, and uncertain information. To support HDMs in humanitarian relief distribution (HRD) decision-making, humanitarian logistics (HL) researchers have developed various mathematical models. These models are, however, specific to disaster scenarios, and most of them are detached from the realities of the field since end-users (mainly practitioners) have been absent in the development process. When tested, these decision-making models were found to be capable of producing good results, but they have not been implemented in practice because of operational inconsistency or complexity (i.e., lack of user-friendliness). Therefore, humanitarian responders are still in need of support systems to assist them in determining effective HRD. A computer-based decision support system (DSS) can fill this need by providing necessary recommendations and suggesting decision alternatives. Hence, developing such DSSs is always the priority in HL.publishedVersio