## 1 Introduction  
In recent years, a tremendous number of studies based on observed evidences or data-based experiments have shown that the number, frequency, and severity of disaster events are sharply increasing around the world [1]. Natural disasters such as Hurricane Katrina in the United States (USA), the tsunami in Asia, or man-made attacks such as the 9/11 terrorist attack in New York in 2001 and the London bombings in 2005 have shown that the use of communications and network connectivity is of vital importance for saving lives [2]. Several other serious outcomes are observed after a disaster; these include social effects such as looting, economic pressures such as loss of tourism industry, etc. [3]. The Wenchuan earthquake of 2008 hit a wide area of Sichuan Province in China, and cost at least 69,227 deaths according to the government. Most social infrastructures, such as transportation, electric power, gas, water, and telecommunication services, suffered serious damages due to the tremor and succeeding disasters, which isolated the inhabitants of the disaster-affected areas from the rest of the world. For quite a long time, the outside could not get any information in the disaster areas. Another one of the large-area disasters undergoing a clear increase in its scales, magnitudes, and consequences are wildfires. In this context, the report presented at the annual meeting of the American Geophysical Union in San Francisco (USA) in late 2012 predicted that the burned area from wildfires in the USA would double in size by 2050 due to warmer and drier conditions in forthcoming decades [4]. This prediction was buttressed by the record of incidences in that same year, with massive fires affecting Colorado and New Mexico [5]. A conclusion of utmost importance for the scope of this work is that all of the above observations lead to the certainty that commanders and decision makers will encounter higher difficulties in the future when allocating resources against disasters due to their simultaneity, co-locality, and interconnection. Decision-making in this context is usually driven by predetermined procedures and/or protocols based on the passive reaction triggered by relative disasters (e.g., traffic jam caused by an accident). The purpose of making decisions lies on the mitigations of costs and casualties, thus demanding the effective management of resources in disaster situations. For instance, [PERSON], et al. in [6] analyzed bidding mechanisms for optimally procuring goods in disaster relief logistics by using an integer programming formulation of the underlying auction operation. [PERSON] and [PERSON] in [7] derived a dynamic time-dependent nonlinear model to quantify the influence of a disaster on supply, demand, and humanitarian logistics, and applied genetic algorithms to infer the optimal logistic plan that would minimize the mismatches between the supplied goods and the demand, as well as the time delay of their delivery. Other references in disaster management include the allocation of critical emergency resources in multi-hazard situations [8; 9; 10], transport and provisioning under uncertainty [11], supply chain logistics [12], and waste management [13], among many others. Based on what has been discussed above, we can conclude that resource allocation is of great important in disaster relief scenarios. This paper elaborates on a particular yet usual resource allocation problem in disaster management: the selection of next-hop node selection in Disaster Area Wireless Networks (DAWNs) [14]. After man-made or natural disasters such as earthquakes, fires, floods, etc., the communication infrastructure may be partly or completely destroyed. Meanwhile, first responders need to communicate and exchange data through networks in disaster areas in order to build the bridge between the front and back of the affected area. The damage of communication links impacts on the process of disaster relief, thus threading the lives and property of the affected refugees.