Resumo (PT):
Abstract (EN):
This paper presents a methodology to locate vehicle base stations using a scenario based optimisation to address daily traffic
and demand changes, which are due to what we define as city dynamics. The model allows us to understand better how these
daily changes affect an urban emergency medical service (uEMS) response system.
The methodology incorporates two steps. The first step uses scenario-based optimisation and survival function theory to
locate vehicle base stations, whereas the second step uses agent-based simulation to assess the solution performance and
compare it with average-period and non-survival prone solutions. The proposed models are tested for different situations using
real data from the city of Porto.
The results of the sensitivity analyses show the importance of understanding the dynamics of cities and how they impact
uEMS response systems. Useful insights regarding the number of stations and the average response time are addressed together
with the minimum number of stations required for different maximum response time limits and different survival coefficients.
Finally, we conclude that a multi-period solution improves response time because it accounts for city dynamics and that a
heterogeneous survival-based approach benefits victims' by properly measuring the system response concerning the victims'
outcome.
Keywords Emergency medical service; Scenario-based optimisation; Simulation; City dynamics; Survival functions; Multiperiod approach
Idioma:
Inglês
Tipo (Avaliação Docente):
Científica
Nº de páginas:
18