Modelo matemático para roteirização de frota heterogênea de ambulâncias com priorização de grupos de pacientes

• Ano de defesa: 2018
• Autor(a) principal: Berger, Gelson Junior Donatti Schimith
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Engenharia Civil; Centro Tecnológico; UFES; Programa de Pós-Graduação em Engenharia Civil
• Palavras-chave em Português: Ambulance Routing Problem; Medical Emergency Services; Emergency Mobile Care Service; Mixed Integer Programming; Problema de Roteirização de Ambulâncias; Serviços de Emergências Médicas; Serviço de Atendimento Móvel de Urgência; Programação Inteira Mista; Emergências médicas - Vitória, Região Metropolitana de (ES); Serviço de ambulância - Levantamentos de rotas; Serviços médicos de emergência; Programação inteira; Engenharia Civil; 624
• Link de acesso: http://repositorio.ufes.br/handle/10/10170

Assisting medical emergencies involve several factors, with high levels of uncertainty. Decisions must be made with high quality and as quickly as possible. Within the operational aspect, the decision about which route an ambulance should take to make it in the shortest time possible at the victim’s place of care can be crucial for the survivor of the patient. The ProKnow-C methodology was used to carry out a selection of the bibliographic portfolio and an analysis of the literature on the Ambulance Routing Problem (ARP). It was identified that there was a gap in the literature for mathematical models on minimizing the time of care of two groups of patients that are served by a heterogeneous fleet of ambulances. An optimization model was proposed using Mixed Integer Programming and implemented using CPlex Optimization Studio 12.7.1 solver software. A case study was proposed in Grande Vitória’s SAMU, where the parameters to run the model were obtained. A total of 243 scenarios were run and the results obtained allowed to identify that the increase in the total amount of ambulances in the system generates a positive impact in the care service time of both patient groups, as well as the increase in the number of ambulances qualified to attend all types of accidents. However, the increase in the number of calls of greater severity patients makes the time of care for this group higher and reduces the time of care of the lower clinical severity group. Regarding the model’s computational time, the values found were unsatisfactory, considering that speed is essential for this type of service.