Humanitarian Logistics Network: Comparison
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This research presents a comprehensive methodology for enhancing humanitarian logistics planning and management in natural disasters, focusing on earthquakes.

Humanitarian Logistics Network (HLN) acts as a coordinating body for humanitarian partners interested in embarking goods or personnel.

  • humanitarian logistics
  • disaster management
  • post-disaster relief logistics

1. Introduction

Disasters caused by natural phenomena, such as earthquakes, are sudden and dangerous events that cause damage to human life. Since the early 2000s until now, more than 7350 disasters have been reported; these affected over 4 billion people and caused more than a million deaths and trillions in economic losses [1]. According to [2], the population affected by a natural disaster will increase in cities with a higher concentration of inhabitants; therefore, urban development requires a managing response and a decision-making plan in the face of a humanitarian crisis. On the other hand, some human actions can magnify the damage of natural disasters; for instance, the vulnerability of households increases the risk, understood as the expected damage from disasters, that they face.
Annually, cataclysms such as earthquakes, hurricanes, volcanic eruptions, and floods claim lives worldwide. Among the most devastating catastrophes of recent decades are the earthquake in Japan with more than 20,033 deaths [3], the Sichuan earthquake in China and the earthquakes in Haiti that affected more than 56 million people in both countries and the Chilean earthquake of 2010 [4]. All these events caused significant damage to the population. According to recent statistics, Iran is the seventh country in the world with the highest risk of earthquakes [5][6]. Evidence shows earthquakes are the most frequent natural catastrophes [7]. Disaster management in an earthquake is one of the most critical issues. In addition to a large number of victims, the economy and health system of affected areas may deteriorate after disasters [8]. In this sense, places like Aceh (Indonesia) have substantially improved their disaster preparedness and mitigation over the years [9].
In Colombia, the consequences of nature’s actions can also be evidenced; according to the study conducted [10], in the last 40 years, more than 28 thousand disaster events were recorded, of which 60% were reported from the 1990s onwards. During 2010 and 2019, a quarter of such records were reported, and a third of the population was affected. In this context, in 1983, Popayan registered an earthquake of 5.5 on the Richter scale; this situation meant a high humanitarian crisis [11]. There were more than 100,000 victims, 1200 injured, and 300 casualties; it is estimated that 2470 houses were destroyed and economic losses of 378 million dollars (0.98% of the G.D.P. of that year) [12]. This municipality is located in the Romeral fault area, which crosses the country from north to south in the Andean zone. This seismological fault originated from the Pacific Ring of Fire. In this case, there is sufficient historical evidence to highlight that if studies, actions, and plans that lead to a significant reduction in risk are not prioritized, disasters such as the one in 1983 could be repeated, which left a large part of the city in ruins [12].
Therefore, given the growing trend of disasters globally [13], it is relevant to keep studying issues related to humanitarian logistics. In addition, it is worth noting the particular requirements of a humanitarian supply chain compared to the traditional one: higher initial demand, the unpredictability of resources, and the relevance of decisions made [14]. From the actors’ perspective involved, the need to go beyond the benefits of theoretical models and incorporate organizational and human systems aspects that significantly affect disaster response is evident. This research seeks to integrate both paradigms by incorporating organizational and institutional aspects into quantitative and qualitative models that address operational problems.

2. Humanitarian Logistics

Humanitarian Logistics (H.L.) is the process of efficiently planning, implementing, and controlling the cost-effective storage of goods and materials and related information from the point of origin to the point of consumption [15]. In addition, it is necessary to have the ability to recognize (detect), determine required resources (seizure), and review strategies to achieve effective supply chain operations in the face of disasters (reconfiguration/transformation) [16]. The H.L. application is essential to improve disaster management, and its development and challenges have become more critical in recent years due to increased activity worldwide [17]. Since 2001, about 500 events have occurred annually, with an average of about 75,000 casualties and more than 200 million people affected. Humanitarian logistics (H.L.) for disaster response has been developed for several decades [18], aiming to improve efficiency and effectiveness in providing aid and assistance to communities affected by natural disasters and humanitarian emergencies. In this context, several studies have analyzed the role and performance of the tasks of each of the members of the organizations in charge of humanitarian aid in different catastrophic events, such as the hurricane that affected the Gulf Coast in the United States [18]. Over time, the application of methodologies and technology [19] has been promoted in research, seeking to optimize logistical processes and improve the capacity to respond to critical situations. However, despite these advances, humanitarian aid organizations still face challenges in the supply chain to reach the disaster-affected area promptly and efficiently and adequately meet the demand [20]. Moreover, the impact of H.L. in emergencies and the location of facilities or shelters are essential parts of the current research [21][22]. It ratifies the relevance of application for each type of calamity because, through this, the negative consequences caused by different disasters can be minimized.

3. Planning

It can be defined as managing and organizing different activities to minimize the impact of natural disasters on a specific population [6]. As mentioned, pre-positioning emergency supplies [23] is a mechanism to increase preparedness for natural disasters. It is a planning tool that determines the location and quantities of the different types of emergency supplies. As reported by [24], an essential component of H.L. is the inventory system since it can ensure an adequate supply of critical supplies to meet the needs of the victims. Another relevant issue is evacuation planning; as mentioned by [25], in an emergency, evacuation is carried out to move people from a dangerous place to a safer one. Ref. [26] raised a robust method of scheduling and routing vehicles for emergency evacuation from wildfires with a study based in Australia. The theory of queuing networks was applied to the first work on disaster planning, as mentioned [27], in such a way that it was sought to design an optimal distribution network mitigating the inherent consequences of a disaster. The application of the multi-hierarchical criterion appeared hand in hand with routing models [14][28] developed a model that maximizes the coverage of the affected regions and minimizes human suffering through a social cost function. For example, some studies presented stochastic models in which the location of the site is chosen to satisfy the demand based on different possible catastrophes [23] or their impacts: Ref. [29] It also included budget restrictions before and after the disaster; the level of service quality [30]. Ref. [31] defined an optimal shelter network that minimizes transportation time while [31] proposing a two-stage stochastic model to consider shelter provision. In [32] a multiperiod resource allocation optimization model was established in this study as an extension of the traditional model from the cross-regional collaborative perspective. Ref. [33] analyzed the operation strategies of specialized rescue teams in emergencies. The teams applied standard procedures for rescue operations. Stakeholders should align their values, purposes, and goals to their strategic planning process since this preparation occurs in an environment with a destabilized infrastructure and poorly competent transport connectivity [6].

4. Response

In 2006, a framework for applying indicators to H.L. processes [34] was created; it highlights the importance of using multimodal transport in response and recovery operations [35]. The heuristic algorithms applied a model in response operations that included routing, vehicle allocation, and merchandise distribution [29]. Natural disasters can cause severe casualties and economic losses, and emergency shelters are effective measures to reduce disaster risks and protect lives. Shelters have functions in different phases of disasters and can be defined as: “A place used for a short stay, ideally no more than a few weeks after the disaster” [36]. These models seek to choose shelters from a given set of alternate locations and provide transportation plans to minimize total costs or evacuation time [16]. They proposed a stochastic model for the distribution of aid and evacuation of victims towards the positioning of temporary care centers, intending to minimize the number of untreated injured and shortages of basic supplies. On the other hand, Ref. [31] used the Stackelberg game to guarantee locations by the communities, where the authorities act as leaders determining the locations of the shelters to minimize the total evacuation time. Ref. [37] formulated a multiobjective location model based on a goal programming approach that considers the uncertainties of damage to infrastructure due to earthquakes, Ref. [38] considered multiple risk objectives, number of sites, unsatisfied demand, and adequacy qualitative of locations. Along this line, Ref. [39] suggested a relief network that offers fixed and temporary hospitals, transfer points, ambulance stations, helicopter stations, and demand points. Ref. [40] in addition, proposed a multi-pronged methodology using an optimization model and multi-criteria decision analysis to pre-position disaster relief supplies. Ref. [41] developed a dynamic model for dispatching and directing vehicles in response to an earthquake, focusing on transporting essential goods to affected areas and the injured to hospitals. Ref. [42] researched a novel and comprehensive algorithm to analyze an emergency location routing problem considering a fast and stable response to different situations. Ref. [42] proposed a multiobjective, multimodal, multi-period stochastic model for managing commodity and casualty logistics in earthquake response.

5. Recovery

It seeks to characterize disaster management at a general level by some international organizations, such as the United Nations Development and Environment Programmes (UNDP-UNEP), which identify four fundamental phases: prevention, preparation, response, and recovery [43]. As defined by many authors, they involve a series of planning and prevention processes, namely: natural risk assessment, prioritization of community objectives, tasks, and activities, identification of standards and indicators to measure efficiency and effectiveness, the establishment of coordination protocols between actors, inventory of local community capacities, the command center for management, means, measurement and evaluation of results, corrective actions to improve the situation generated and alert system [44]. The quality and speed of logistics activities in the recovery phase impact how the community rebuilds from a disaster; therefore, these studies should be presented as a basis for long-term development programs and public policies, as suggested by [45]. In the context of post-disaster recovery, the quality and speed of logistics activities play a crucial role in the reconstruction of an affected community. In this sense, it is emphasized that the economy should be reactivated considering the principles of humanitarian logistics [46]. Specifically, assessing the demand for humanitarian aid is a key factor in planning recovery and effectively distributing resources.

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