Efficiency and fairness in ambulance planning

Mei, R.D. van der [Promotor]Bhulai, S. [Promotor

Mensenlevens Redden met Operations Research: Dynamisch Ambulance Management

In noodsituaties waarin elke seconde telt, is het tijdig ter plaatse zijn van een ambulance van levensbelang. Een veelbelovende manier om de aanrijtijden van ambulances te verkleinen is Dynamisch Ambulance Management, waarbij ambulances geen vaste standplaats hebben, maar slim en dynamisch over de regio kunnen worden vespreid afhankelijk van de voertuig- en incidentlocaties. In het kader van het project “Van Reactieve naar Proactieve Planning van Ambulancediensten”, kortweg REPRO, hebben CWI en TU Delft nieuwe methoden ontwikkeld voor een optimale dynamische spreiding van ambulances over een verzorgingsgebied. De resultaten zijn veelbelovend en worden momenteel uitgetest in een pilot in samenwerking met GGD Flevoland

Real-time ambulance relocation: Assessing real-time redeployment strategies for ambulance relocation

Providers of Emergency Medical Services (EMS) are typically concerned with keeping response times short. A powerful means to ensure this, is to dynamically redistribute the ambulances over the region, depending on the current state of the system. In this paper, we provide new insight into how to optimally (re)distribute ambulances. We study the impact of (1) the frequency of redeployment decision moments, (2) the inclusion of busy ambulances in the state description of the system, and (3) the performance criterion on the quality of the distribution strategy. In addition, we consider the influence of the EMS crew workload, such as (4) chain relocations and (5) time bounds, on the execution of an ambulance relocation. To this end, we use trace-driven simulations based on a real dataset from ambulance providers in the Netherlands. In doing so, we differentiate between rural and urban regions, which typically face different challenges when it comes to EMS. Our results show that: (1) taking the classical 0-1 performance criterion for assessing the fraction of late arrivals only differs slightly from related response time criteria for evaluating the performance as a function of the response time, (2) adding more relocation decision moments is highly beneficial, particularly for rural areas, (3) considering ambulances involved in dropping off patients available for newly coming incidents reduces relocation times only slightly, and (4) simulation experiments for assessing move-up policies are highly preferable to simple mathematical models

Benchmarking online dispatch algorithms for Emergency Medical Services

Providers of Emergency Medical Services (EMS) face the online ambulance dispatch problem, in which they decide which ambulance to send to an incoming incident. Their objective is to minimize the fraction of arrivals later than a target time. Today, the gap between existing solutions and the optimum is unknown, and we provide a bound for this gap.Motivated by this, we propose a benchmark model (referred to as the offline model) to calculate the optimal dispatch decisions assuming that all incidents are known in advance. For this model, we introduce and implement three different methods to compute the optimal offline dispatch policy for problems with a finite number of incidents. The performance of the offline optimal solution serves as a bound for the performance of an - unknown - optimal online dispatching policy.We show that the competitive ratio (i.e., the worst case performance ratio between the optimal online and the optimal offline solution) of the dispatch problem is infinitely large; that is, even an optimal online dispatch algorithm can perform arbitrarily bad compared to the offline solution. Then, we performed benchmark experiments for a large ambulance provider in the Netherlands. The results show that for this realistic EMS system, when dispatching the closest idle vehicle to every incident, one obtains a fraction of late arrivals that is approximately 2.7 times that of the optimal offline policy. We also analyze another online dispatch heuristic, that manages to reduce this gap to approximately 1.9. This constitutes the first quantification of the gap between online and offline dispatch policies

Klinik UPSR 2016

Calon Ujian Pencapaian Sekolah Rendah (UPSR) akan mendapat tip menjawab soalan secara berkesan menerusi Klinik UPSR BH Didik (Fasa 2).Program ini berberituk seminar dengan ceramah selama tiga jam setengah setiap subjek

Centralized multi-visitor trip planning with activity reservations in crowded destinations

We study the problem of centralized planning of leisure trips in congested areas for visitor groups with reservations for activities. We develop an algorithm that through a combination of customization and coordination can improve average happiness considerably. Extensive numerical experimentation with both synthetic and real-life data show that our algorithm strongly outperforms the classical First-Come-First-Served reservation policy, both in terms of visitor happiness and in terms of fairness among visitors. Moreover, our results show that our algorithm leads to good solutions for small-sized problem instances (with errors typically within 5%–10% from an optimal solution obtained via Integer Linear Programming). Finally, the computational effort with regard to number of visitors is bounded by the capacity and the number of activities, while the increase in computation time for the number of attractions is bounded by the average number of activities that fit into a trip. As a result, our approach leads to good solutions within minutes in realistic settings with more than 10 thousand visitors a day