Towards Designing an Assistant for Semi-Automatic EMS Dispatching

Many Emergency Medical Service (EMS) systems worldwide handle emergency rescues as well as patient transports and dispatchers need to assign ambulances to incidents manually throughout the day. The management of the complex system together with the manual assignments can easily create stress for and pressure on the dispatchers. Mathematical algorithms can help improving the dispatching quality, but then dispatchers still need to choose the best-fitting algorithm and furthermore, trust the algorithm’s dispatching suggestion. We propose an assistant that can support the EMS dispatchers. The assistant offers explanations for the choice of the algorithm as well as the dispatching suggestion in order to increase the dispatchers’ trust and decrease their stress. We ground the assistant’s design in Information Systems as well as Operations Research literature and thus, show how interdisciplinary service research can contribute in designing artefacts for complex service systems to solve real-world problems

Modelo Matemático para Roteirização de Frota Heterogênea de Ambulâncias Com Priorização de Grupos de Pacientes

O atendimento de emergências médicas envolve diversos fatores, com altos graus de incerteza. As decisões têm que ser obtidas de forma rápida e com alta qualidade. Dentro do aspecto operacional, a decisão de qual rota uma ambulância deve tomar para chegar ao local de atendimento de uma vítima no menor tempo possível pode ser crucial para a sobrevivência do paciente. Foi utilizada a metodologia ProKnow-C para realizar uma seleção do portfólio bibliográfico e uma análise da literatura do Problema da Roteirização de Ambulâncias (PRA). Foi identificado que havia uma lacuna na literatura para modelos matemáticos de minimização do tempo de atendimento de dois grupos de pacientes que são atendidos por uma frota heterogênea de ambulâncias. Um modelo de otimização foi proposto, utilizando Programação Inteira Mista, e implementado usando o software de otimização CPlex Optimization Studio 12.7.1. Foi proposto um estudo de caso no SAMU da Grande Vitória, onde foram obtidos os parâmetros para execução do modelo. Foram executados 243 cenários e os resultados obtidos permitiram identificar que o aumento do número total de ambulâncias no sistema gera um impacto positivo nos tempos de atendimento de ambos grupos de chamados, assim como o aumento do número de ambulâncias capacitadas para atender todos tipos de acidentes. Entretanto, o aumento do número de chamados de pacientes de maior gravidade faz com que o tempo de atendimento para esse grupo seja maior e reduz o tempo de atendimento do grupo de menor gravidade. Em relação ao tempo de execução do modelo, os valores encontrados não foram satisfatórios, considerando que a rapidez é essencial para esse tipo de serviço. Palavras-chave: Problema de Roteirização de Ambulâncias; Serviços de Emergências Médicas; Serviço de Atendimento Móvel de Urgência; Programação Inteira Mista

Distribuição dos utentes na Rede Nacional de Cuidados Continuados Integrados do Alentejo

Mestrado em Decisão Económica e EmpresarialEsta pesquisa aborda a Rede Nacional de Cuidados Continuados Integrados (RNCCI) em Portugal, focando-se na especialidade de unidade de cuidados continuados de internamento com o objetivo de criar uma distribuição dos utentes pelas unidades da zona do Alentejo. Após recolha dos dados, disponibilizados na internet, procedeu-se ao seu estudo e tratamento. Seguidamente, num ambiente de planeamento a nível tático, procedeu-se à distribuição dos utentes conforme a área inserida no estudo e a quantidade de camas que cada zona da referida área tem disponível ao ano. Esta distribuição foi feita minimizando o custo total de internamentos nas respetivas zonas, custo este que contabiliza as despesas relacionadas com o transporte e internamento para todas as unidades abrangidas pelo estudo. De modo a aplicar os conhecimentos adquiridos no mestrado, no que toca a Investigação Operacional, utiliza-se neste estudo um modelo de otimização, particularmente, um modelo de tipo de transportes de programação linear.O software utilizado na resolução do problema foi o Solver do Microsoft Office Excel. Com esta abordagem ao problema de planeamento de distribuição de utentes na RNCCI do Alentejo, pretende-se dar ênfase ao progresso da RNCCI em Portugal, disponibilizando uma ferramenta que pode ser usada pelos gestores no âmbito da saúde.This research reports the National Network for Continuous Care (RNCCI), in Portugal, focusing on admission of patients in continuous care units. The intent of this work is to create a distribuition network for users of the Alentejo region. After data collection, available on the internet, we proceeded with the study and treatment of data. Afterwards, in the tactical planning setting, we proceeded with the distribution of users depending on the residential area and the number of beds available per year in each zone. This distribution was performed to reduce the total cost of hospitalization, a cost wich covers expenses related to transport and admission in the units covered by the study. In order to deepen the knowledge acquired in the master degree courses, with respect to operational research, in this study an optimization model is developed a linear programming transportation problem. The software used for solving the problem was the Solver of Microsoft Office Excel. With this approach to the problem of planning the distribution of users in the RNCCI of Alentejo region, we intend to emphasize the progress of the RNCCI in Portugal, and provide a tool that can be used by health policy makers.info:eu-repo/semantics/publishedVersio

Dynamic vehicle routing problems: Three decades and counting

Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics.© 2015 Wiley Periodicals, Inc

Scheduling non-urgent patient transportation while maximizing emergency coverage

Many ambulance providers operate both advanced life support (ALS) and basic life support (BLS) ambulances. Typically, only an ALS ambulance can respond to an emergency call, whereas non-urgent patient transportation requests can either be served by an ALS or a BLS ambulance. The total capacity of BLS ambulances is usually not enough to fulfill all non-urgent transportation requests. The remaining transportation requests then have to be performed by ALS ambulances, which reduces the coverage for emergency calls. We present a model that determines the routes for BLS ambulances while maximizing the remaining coverage by ALS ambulances. Different from the classical Dial-A-Ride Problem, only one patient can be transported at a time and not all request are known in advance. Throughout the day, new requests arrive and we present an online model to deal with these requests

Branch-and-Price-and-Cut for the Active-Passive Vehicle-Routing Problem

This paper presents a branch-And-price-And-cut algorithm for the exact solution of the active-passive vehicle-routing problem (APVRP). The APVRP covers a range of logistics applications where pickup-And-delivery requests necessitate a joint operation of active vehicles (e.g., trucks) and passive vehicles (e.g., loading devices such as containers or swap bodies). The objective is to minimize aweighted sum of the total distance traveled, the total completion time of the routes, and the number of unserved requests. To this end, the problem supports a flexible coupling and decoupling of active and passive vehicles at customer locations. Accordingly, the operations of the vehicles have to be synchronized carefully in the planning. The contribution of the paper is twofold: First, we present an exact branch-And-price-And-cut algorithm for this class of routing problems with synchronization constraints. To our knowledge, this algorithm is the first such approach that considers explicitly the temporal interdependencies between active and passive vehicles. The algorithm is based on a nontrivial network representation that models the logical relationships between the different transport tasks necessary to fulfill a request as well as the synchronization of the movements of active and passive vehicles. Second, we contribute to the development of branch-And-price methods in general, in that we solve, for the first time, an ng-path relaxation of a pricing problem with linear vertex costs by means of a bidirectional labeling algorithm. Computational experiments show that the proposed algorithm delivers improved bounds and solutions for a number of APVRP benchmark instances. It is able to solve instances with up to 76 tasks, four active, and eight passive vehicles to optimality within two hours of CPU time

A mathematical programming approach for dispatching and relocating EMS vehicles.

We consider the problem of dispatching and relocating EMS vehicles during a pandemic outbreak. In such a situation, the demand for EMS vehicles increases and in order to better utilize their capacity, the idea of serving more than one patient by an ambulance is introduced. Vehicles transporting high priority patients cannot serve any other patient, but those transporting low priority patients are allowed to be rerouted to serve a second patient. We have considered three separate problems in this research. In the first problem, an integrated model is developed for dispatching and relocating EMS vehicles, where dispatchers determine hospitals for patients. The second problem considers just relocating EMS vehicles. In the third problem only dispatching decisions are made where hospitals are pre-specified by patients not by dispatchers. In the first problem, the objective is to minimize the total travel distance and the penalty of not meeting specific constraints. In order to better utilize the capacity of ambulances, we allow each ambulance to serve a maximum of two patients. Considerations are given to features such as meeting the required response time window for patients, batching non-critical and critical patients when necessary, ensuring balanced coverage for all census tracts. Three models are proposed- two of them are linear integer programing and the other is a non-linear programing model. Numerical examples show that the linear models can be solved using general-purpose solvers efficiently for large sized problems, and thus it is suitable for use in a real time decision support system. In the second problem, the goal is to maximize the coverage for serving future calls in a required time window. A linear programming model is developed for this problem. The objective is to maximize the number of census tracts with single and double coverage, (each with their own weights) and to minimize the travel time for relocating. In order to tune the parameters in this objective function, an event based simulation model is developed to study the movement of vehicles and incidents (911 calls) through a city. The results show that the proposed model can effectively increase the system-wide coverage by EMS vehicles even if we assume that vehicles cannot respond to any incidents while traveling between stations. In addition, the results suggest that the proposed model outperforms one of the well-known real time repositioning models (Gendreau et al. (2001)). In the third problem, the objective is to minimize the total travel distance experienced by all EMS vehicles, while satisfying two types of time window constraints. One requires the EMS vehicle to arrive at the patients\u27 scene within a pre-specified time, the other requires the EMS vehicle to transport patients to their hospitals within a given time window. Similar to the first problem, each vehicle can transport maximum two patients. A mixed integer program (MIP) model is developed for the EMS dispatching problem. The problem is proved to be NP-hard, and a simulated annealing (SA) method is developed for its efficient solution. Additionally, to obtain lower bound, a column generation method is developed. Our numerical results show that the proposed SA provides high quality solutions whose objective is close to the obtained lower bound with much less CPU time. Thus, the SA method is suitable for implementation in a real-time decision support system

A tabu search heuristic for the dynamic transportation of patients between care units

International audienceThe problem studied in this paper stems from a real application to the transportation of patients in the Hospital Complex of Tours (France). The ambulance central station of the Hospital Complex has to plan the transportation demands between care units which require a vehicle. Some demands are known in advance and the others arise dynamically. Each demand requires a specific type of vehicle and a vehicle can transport only one person at a time. The demands can be subcontracted to a private company which implies high cost. Moreover, transportations are subject to particular constraints, among them priority of urgent demands, disinfection of a vehicle after the transportation of a patient with contagious disease and respect of the type of vehicle needed. These characteristics involve a distinction between the vehicles and the crews during the modeling phase. We propose a modeling for solving this difficult problem and a tabu search algorithm inspired by Gendreau et al. (1999). This method supports an adaptive memory and a tabu search procedure. Computational experiments on a real-life instance and on randomly generated instances show that the method can provide high-quality solutions for this dynamic problem with a short computation time

PROGRAMAÇÃO E ROTEIRIZAÇÃO DINÂMICA DE VEÍCULOS APLICADO AO SERVIÇO DE TRANSPORTE DE CADEIRANTES

Este trabalho tem como objetivo desenvolver um sistema de suporte à decisão para programação e roteirização de veículos dedicados ao transporte de pessoas (Dial-a-Ride Problem) cadeirantes, considerando fatores dinâmicos. Para isso, apresenta uma revisão bibliográfica com as principais leis e estatísticas relacionadas ao transporte de cadeirantes, os principais conceitos e métodos de programação e roteirização dinâmica de veículos (Dynamic Routing Problem DRP) e conceitos e métodos de desenvolvimento de sistemas de informação. Entre os métodos de programação e roteirização dinâmica apresentados, sobressai a heurística inserção, método que é o referencial para esta pesquisa. O desenvolvimento do sistema em questão se deu na linguagem VBA (Visual Basic for Applications), sendo testado com dados reais de 20 dias de operação de um serviço de transporte de cadeirantes localizado na região da Grande Vitória, o Serviço Especial Mão na Roda, o qual conta com 3.525 usuários cadastrados em julho de 2014. Para a realização dos testes do sistema proposto e análise de suas saídas, recorreu-se à avaliação dos resultados da programação e roteirização das 20 amostras selecionadas com base na distância adicionada nos roteiros para o atendimento das novas solicitações, no tempo de processamento e na quantidade de solicitações demandadas e passíveis de inserção segundo resultados do sistema apresentado. Além disso, houve comparação dos dados com os resultados das programações empíricas utilizadas pela central de programação em que se procedeu ao estudo de caso. Os resultados mostraram que o sistema proposto é capaz de realizar a inserção das solicitações de forma dinâmica nos roteiros existentes, com um tempo computacional médio de cinco segundos por solicitação