Dispatching Fire Trucks under Stochastic Driving Times

In this paper we discuss optimal dispatching of fire trucks, based on a particular dispatching problem that arises at the Amsterdam Fire Department, where two fire trucks are send to the same incident location for a quick response. We formulate the dispatching problem as a Markov Decision Process, and numerically obtain the optimal dispatching decisions using policy iteration. We show that the fraction of late arrivals can be significantly reduced by deviating from current practice of dispatching the closest available trucks, with a relative improvement of on average about $20\%$, and over $50\%$ for certain instances. We also show that driving-time correlation has a non-negligible impact on decision making, and if ignored may lead to performance decrease of over $20\%$ in certain cases. As the optimal policy cannot be computed for problems of realistic size due to the computational complexity of the policy iteration algorithm, we propose a dispatching heuristic based on a queueing approximation for the state of the network. We show that the performance of this heuristic is close to the optimal policy, and requires significantly less computational effort.Comment: Submitted to Computers and Operations Research (December 08, 2018

Analyse des politiques d’affectation d’un service préhospitalier d’urgence par simulation

RÉSUMÉ : Lorsqu’une urgence médicale survient, le premier réflexe est de composer le numéro d’appel d’urgence. Aussitôt, un processus complexe s’enclenche menant à l’arrivée d’une équipe de techniciens ambulanciers paramédics. Leurs interventions rapides peuvent éviter des drames et sauver des vies. Les services préhospitaliers d’urgence (SPU) sont les organisations derrière ces interventions d’urgence. Leur mission est de fournir des soins préhospitaliers et du transport ambulancier de qualité. La vitesse à laquelle les SPU répondent aux demandes, leurs temps de réponse (TR), est un indicateur important de la qualité de leur service comme l’état de santé des patients peut se dégrader rapidement en l’absence de soins. De plus, même pour les patients non urgents, des temps de réponse courts sont désirables comme les patients souhaitent recevoir de l’aide rapidement. L’objectif de ce mémoire est de développer un modèle de simulation d’un SPU et de l’utiliser pour développer et pour tester des règles de gestion capables de réduire les temps de réponse. Plus précisément, nous modélisons Urgences-santé, le SPU responsable de Montréal et de Laval, et proposons plusieurs politiques pour améliorer leurs décisions d’affectations. Le modèle est développé en étroite collaboration avec le SPU permettant ainsi de bâtir un modèle réaliste. L’affectation consiste normalement à choisir l’ambulance à attribuer à chaque patient parmi celles disponibles. Nous proposons d’étendre cette définition en considérant non seulement les ambulances disponibles, mais également celles qui sont indisponibles. En effet, il est possible que ces ambulances occupées soient capables de répondre à un appel plus rapidement que les ambulances libres. Cette approche a été très peu considérée dans la littérature. Nous permettons l’affectation d’ambulances indisponibles dans trois cas : avant le début des quarts de travail, pendant la pause repas et pendant le transfert de patient à l’hôpital. D’après notre modèle, l’inclusion du premier et du troisième groupe dans l’affectation des appels de basses priorités permet de réduire leurs TR de 4.2% et 7.3% respectivement. La deuxième méthode n’améliore pas les temps de réponse que nous expliquons par la redondance entre la position des ambulances qui prennent leur pause repas avec celles des ambulances disponibles. De plus, nous proposons d’utiliser les ambulances nouvellement disponibles pour améliorer les affectations de basses priorités ce qui mène à une diminution de leurs TR de 7.3%. Au meilleur de notre connaissance, nous sommes les premiers à utiliser cette politique pour des appels de basses priorités. Ces politiques peuvent être combinées, ce qui peut amener des diminutions des TR de basses priorités allant jusqu’à 8.2%. L’effet de ces politiques sur les appels de hautes priorités est négligeable ou nul. Ces gains sont réalisés par rapport aux règles actuelles d’Urgences-santé dont la politique d’affectation est déjà sophistiquée. Ces résultats nous amènent à recommander l’ajout de ces politiques à leurs politiques. Elles pourraient également être bénéfiques à d’autres SPU. Notre modèle de simulation a le potentiel d’être appliqué à des politiques de gestion des SPU autres que celles d’affectation. En effet, les politiques de localisation et de relocalisation, de sélection du centre hospitalier, de gestion des effectifs et de spécialisation des ressources pourraient être étudiées à l’aide du modèle.----------ABSTRACT : When faced with a medical emergency, our first instinct is to call 911. This puts in motion a complex process that leads to the arrival of one or more teams of emergency responders. Their intervention can save lives and avoid tragedies. Behind the scenes, emergency medical services (EMS) manage these teams. The goal of these organizations is to provide quality emergency prehospital care. The response time (RT), defined as the time required to reach a patient, is a primary quality indicator, because patients’ conditions can deteriorate rapidly. Even for non-urgent requests, fast RT is important as patients expect a quick reaction. The goal of this thesis is to develop a simulation model of an EMS and to use it to measure the impact of new strategies on response time. The model is based on Urgences-santé, the EMS for Montreal and Laval Islands. We propose and evaluate policies to improve their dispatching performance. The model was developed in collaboration with the Urgences-santé, which maximises its fidelity. Dispatching policies define which ambulance among all available ambulances is chosen to answer a call. We extended this definition to include “near-to-be-available” ambulances as they are sometimes able to reach a call faster than currently available ambulances. This has sparely been done in the literature. Ambulances are considered “near-to-be-available” during three periods: before the beginning of a shift, during the team’s lunch breaks, and during transfer of care at the hospital. Using our simulation model, we found that considering the first and third groups in dispatching for low priority calls reduces RT by 4.2% and 7.3% respectively. Considering the second group did not yield improvement to RT, as the locations of ambulances during lunch breaks were too similar to the locations of available ambulances. In addition, we evaluated a wholly novel strategy to reducing RT based on replacing alreadydispatched ambulances with newly-available ambulances to replace ambulances assigned to low priority calls which reduces RT. To be best of our knowledge, this has never been done before. This policy reduced RT for low-priority requests by 7.3%. Combining those policies improved performance further, yielding RT reductions of up to 8.2% for low-priority calls. It is important to note that all evaluated policies had no or negligible impact on the RT for high-priority calls. We recommend the adoption of those policies to Urgences-santé. They might also be applicable to other EMS systems. The simulation model applications are not limited to the evaluation of dispatching policies. It could be used to evaluate new policies for location and elocation, hospital selection, staff management, and resources specialization

Transportation Systems Analysis and Assessment

The transportation system is the backbone of any social and economic system, and is also a very complex system in which users, transport means, technologies, services, and infrastructures have to cooperate with each other to achieve common and unique goals.The aim of this book is to present a general overview on some of the main challenges that transportation planners and decision makers are faced with. The book addresses different topics that range from user's behavior to travel demand simulation, from supply chain to the railway infrastructure capacity, from traffic safety issues to Life Cycle Assessment, and to strategies to make the transportation system more sustainable

Modelagem matemática para localização de bases de despacho de veículos de resgate: um estudo de caso no município do Rio de Janeiro

The Emergency Medical Services are considered critical elements of modern health services, mainly to ensure that the level of service is appropriate for the population of the region that serve, as it depends on the service the worsening or not of the victim’s health condition. We applied Facility Location Problems, in this context, to indicate strategic points to the location of rescue vehicles dispatching bases attending emergency calls. In the city of Rio de Janeiro, this type of service is the responsibility of the Military Fire Department of the State of Rio de Janeiro, which has units distributed throughout the territory, where the rescue vehicles are dispatched. Therefore, the objective of this work is to propose a mathematical modeling to support the planning of the location of rescue vehicles dispatching bases, focusing on the maximization of the population coverage and different types of occurrences recorded and the minimization of the number of dispatch bases opened and the distance between the dispatch bases and the demand points. Bibliographic and documentary researches were carried out with the purpose of understanding the main characteristics of the location / allocation of ambulance dispatch bases and the main mathematical models of facilities location. Tests were implemented for 11 scenarios with variations in the number of bases and vehicles used which, with the help of georeferencing tools, allowed us to evaluate the coverage and service time for each base in each scenario.Os Serviços Médicos de Emergência são considerados elementos críticos dos sistemas de saúde, pois necessitam assegurar que seu nível de serviço esteja adequado à população a qual serve, uma vez que dele depende o agravamento ou não do estado de saúde da vítima. Neste contexto, os Problemas de Localização de Facilidades vêm sendo aplicados com a finalidade de indicar pontos estratégicos para a localização de bases de veículos que realizam o atendimento às chamadas de emergência. No município do Rio de Janeiro este tipo de serviço é de responsabilidade do Corpo de Bombeiros Militar, que possui unidades distribuídas ao longo do território, de onde são despachados os veículos de resgate. Sendo assim, o objetivo deste trabalho é propor uma modelagem matemática para subsidiar o planejamento da localização de bases de despacho de veículos de resgate, que leve em conta a maximização da população coberta e dos diferentes tipos de ocorrência registrados e a minimização do número de bases de despacho abertas e da distância entre a base de despacho e o ponto de demanda. Pesquisas bibliográficas e documentais foram realizadas com o intuito de compreender as principais características da localização/alocação de bases de despacho de ambulâncias e dos principais modelos matemáticos de localização de facilidades. Foram implementados testes para 11 cenários, com variações no número de bases e de veículos utilizados que, com o auxílio de ferramentas de georreferenciamento, possibilitaram a análise da cobertura e do tempo de atendimento para cada base, em cada cenário

Space benefits: The secondary application of aerospace technology in other sectors of the economy

Over 580 examples of the beneficial use of NASA aerospace technology by public and private organizations are described to demonstrate the effects of mission-oriented programs on technological progress in the United States. General observations regarding technology transfer activity are presented. Benefit cases are listed in 20 categories along with pertinent information such as communication link with NASA; the DRI transfer example file number and individual case numbers associated with the technology and examples used; and the date of the latest contract with user organizations. Subject, organization, geographic, and field center indexes are included

On Contested Shores

Perhaps no prediction has been as consistently made—and as consistently wrong—as the imminent death of amphibious operations. Whatever the changes in warfare and technology, the necessity of amphibious force projection endures, long outliving those who claim its time has passed. Changes in how amphibious operations are conducted, however, are just as consistent. This essential contributed volume arrives at a vital point of transition. These essays highlight both changes and continuities, examining historical amphibious operations as early as the sixteenth century to the near future, describing both lesser-known cases and offering more nuanced views of famous campaigns, such as Gallipoli and Normandy. With the release of the U.S. Marine Corps’ Force Design 2030, this volume gives historians, theorists, and practitioners an opportunity to ground the coming changes in the historical context as they seek to find out what it takes to win on contested shores

Virginia Commonwealth University Courses

Listing of courses for the 2018-2019 year