Assignments of Collaborative Rescue Units during Emergency Response

Assignments of Collaborative Rescue Units during Emergency Response

Felix Wex (Information Systems Research, University of Freiburg, Breisgau, Germany), Guido Schryen (Information Systems Research, University of Regensburg, Breisgau, Germany) and Dirk Neumann (Information Systems Research, University of Freiburg, Breisgau, Germany)
DOI: 10.4018/ijiscram.2013100104


Decision support systems play an increasingly important role in disaster management research. Coordination of rescue units during disaster response is one of the many areas which may benefit from this development. Time pressure, resource shortages, different capabilities of rescue units and the interdependence of scheduling and allocation tasks belong to the key challenges which emergency operation centers have to cope with. This paper proposes a non-linear optimization model and suggests a Monte Carlo-based heuristic solution procedure. The authors computationally benchmark their heuristic with a procedure that is applied in practice. Results of the authors' study show that the Monte-Carlo heuristic is superior to the state-of-the art approach in terms of aggregated harm by up to 40%. However, the authors' simulations also reveal that the time their heuristic needs to process medium-sized instances (100 incidents, 50 rescue units) on a PC is a few hours and that more powerful real-time computing capabilities are required.
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1. Introduction

Natural disasters, including earthquakes, Tsunamis, floods, hurricanes, and volcanic eruptions, have caused tremendous harm and continue to threaten millions of humans and various infrastructure capabilities each year. For example, according to the World Disaster Report of the International Federation of Red Cross and Red Crescent Societies (IFRC, 2010), the megathrust earthquake centered near Sumatra on December 26, 2004, generated a tsunami that resulted in more than 220,000 deaths, the tropical cyclone Nargis on May 2, 2008, lead to almost 140,000 deaths, and the Haiti earthquake on January 12, 2010 caused more than 220,000 deaths. Over all natural disasters within the period 2000-2009, the estimated number of people killed amounted to almost 1 million and the estimated economic damage caused by natural disasters was calculated to almost US$ 1,000 billion, respectively.

Immediate consequences of mid- to large-scale natural disasters (e.g. superregional earthquakes) can often be characterized by (a) an unknown large number of incidents (casualties, damage), (b) multiple, differently skilled rescue teams sent from all over the world, and (c) severe time constraints due to finite rescue times and ever-changing situations. The hidden challenge of natural disaster management (NDM) is to accept, and ideally to be prepared for, these characteristics by satisfying the special needs that are imposed by the set of incidents. This study attempts to tackle these characteristics by deterministically investigating different sets of scenarios each with different numbers of incidents and rescue units.

We use the term “incident” as a proxy for all synonyms indicating any immediate event of damage or loss caused by a natural disaster or its harmful consequences.

According to the literature (Ajami & Fattahi, 2009; Chen et al., 2008; Hale, 1997; IFRC, 2010; Turoff, 2002), challenges and activities of natural disaster management can be classified along the pre-disaster phase (preparedness), the during-disaster phase (response), and the post-disaster phase (recovery) which can be arranged in a life-cycle (Chen et al., 2008). Jennex (2007, p. 2) further distinguishes two phases during response: the immediate response phase “consists of confirming the emergency, generating early warning notices, [and] initiating preplanned initial”. The emergency response phase “implements the emergency response plan and begins coordinating responders and other resources. Additionally, this phase is the command and control phase that requires the emergency response team to monitor conditions and to coordinate response accordingly.”

In this paper, we focus on the response phase(s) of NDM. Effective and efficient coordination efforts during emergency response are regarded as one of the critical tasks for emergency operations centers (EOCs). This fundamental challenge imposed on commanders is typically aggravated due to the lack of centralized command structure, which results from the involvement of many heterogeneous aid organizations, such as the Red Cross, technical relief organizations, and national guards (Schimmelpfennig, 2010). In practice, the involvement of these organizations with different cultural backgrounds, disaster response policies, resources, and capabilities entails a distributed planning and implementation of response actions. It is not astonishing that this organizational patchwork results in overall inefficient disaster response operations and redundancies in commands.

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