The number of people affected by humanitarian crises has greatly increased over the past decade, leading to unprecedented challenges for the humanitarian system. With the increasing impact of disasters, an effective response strategy becomes obligatory. Disasters can be triggered by natural, political, or economic events, their occurrence can destroy the very infrastructure of a country affecting the social, economic, and physical supports of the society. Unlike slowonset disasters, the sudden ones give responders a very short time to react and prevent further damage. Considering the urgency, uncertainty, and complexity associated with managing disasters, enhancements in logistics and supply chain management directly affects the ability of humanitarian organisations to respond and improve overall effectiveness of the response. Disaster response can be extraordinarily challenging in a developing country due to insufficient resources in the immediate aftermath, poor governance, weak infrastructure, damages to infrastructure and a general lack of information, including a response plan and knowledge of the socioeconomic circumstances in affected areas. Hence, being prepared for disasters is critical to the success of humanitarian response efforts.
The concept of planning or preparedness encompasses outlining a set of actions to be taken in the event of a disaster. It is essential to anticipate problems that may occur in the supply chain at an early stage. Put simply, appropriate preparedness is critical for a timely, competent, efficient, and costeffective emergency response (McGuire, 2001). Preparedness may include developing a disaster response framework, prepositioning emergency relief and rescue materials, as well as training and educating the public. Implemented properly, a combination of these strategies can save many lives and minimise suffering. Among the various aspects of preparedness, we focus on prepositioning relief and rescue materials since doing so significantly reduces the time needed to take action following a disaster.
Location selection plays a vital role in ensuring the success of a prepositioning strategy. Placing facilities far from potential demand points might lead to longer delivery times, but being closer to demand nodes exposes them to disasters. Striking the proper balance is key. Facility location models in humanitarian logistics determine the most suitable sites for prepositioning inventories by considering several stochastic as well as deterministic factors; these include cost, response time, location safety, demand coverage, and distance. Facility location models are classified according to their purpose such as evacuation operations, stock prepositioning, or joint stock prepositioning and relief distribution. The term facility is used interchangeably with warehouse in this study. A warehouse can be viewed as permanent or temporary, based on the length of the operation. The placement of permanent warehouses is often a longterm strategic decision meant to anticipate disasters since these facilities involve major capital investments and have farreaching effects. Permanent warehouses include those of the United Nations Humanitarian Response Depot (UNHRD), a global network of strategically located sites in Panama, the United Arab Emirates, Italy, Spain, Malaysia, and Ghana. In contrast, temporary warehouses are set up only after a disaster strikes, usually in the form of mobile storage units or using existing homes as makeshift.
Nepal is a landlocked country in South Asia. The country is prone to various types of natural calamities due to its fragile geophysical structure, which is characterized by very high peaks, complex geology, active tectonic processes, unplanned settlements, variable climatic conditions, and weak economic and political circumstances (ADPC 2010). Every year numerous floods, landslides, fires, epidemics, avalanches and other natural and human made crises causes loss of hundreds of lives and billions of rupees' worth of property. The earthquakes of 1934, 1980, 1988, and 2015 and the floods of 1993 and 2008 were particularly devastating; countless human lives were lost, physical property ruined, and the development process of the entire country adversely affected. Currently with 25.2% of the population living under the national poverty line (ADB 2016), responding to a disaster without prior preparation can severely impact emergency response.
In this study, we focus determining the location of Mobile logistics hubs (MLH's) with the aim of increasing efficiency and effectiveness of emergency response operations. A MLH is defined as a place predesignated for storing emergency logistics and emergency telecommunication equipment. The main aim of establishing an MLH is to preposition logistics equipments including Mobile Storage Units (MSU's) to establish a relief logistics operation center at a remote location near to the disasteraffected area(s). The objective is to quickly establish an operation center to function as a humanitarian platform for management of disaster relief items with the availability of communication systems. MLHs are to be strategically located in different parts of Nepal with the ability to cover districts vulnerable to suddenonset disasters like flood, landslide, and earthquake. In this study, MLHs and PODs are considered at district level granularity due to the input data being at the same level.
Table 1 shows the statistics for different disasters in Nepal and the number of lives lost between the years 1900 and 2016, illustrating that floods, landslides, and earthquakes are the most common types of suddenonset crises and claim the highest number of lives.
Many studies have addressed the importance of preparedness and the need for prepositioned warehouses in humanitarian relief logistics. Although research on facility location problem is abundant in the domain of humanitarian operations (Balcik and Beamon 2008; Dessouky, Murali, and OrdoAez 2009; Rawls and Turnquist 2010; Campbell and Jones 2011; Roh et al. 2015), reviews of existing studies show a general lack of attention to countryspecific situations. It is rare to come across investigations that focus on location problems and consider multiple disaster vulnerabilities, the availability of basic data, factors unique to the nation being examined, and which contain reflections on the current state of disaster preparedness in the country. Hence, our main contribution lies in addressing this gap in literature for facility location problem using real data from Nepal, with the aim of reducing disaster vulnerability by increasing preparedness. Our overall objective is to determine the number of MLHs required and their optimal locations where emergency relief materials can be prepositioned across Nepal. We use a deterministic model with a single objective. We consider three factors unique to Nepal: (1) transportation accessibility, (2) level of development and (3) disaster vulnerability. These three factors are introduced as constraints in the mathematical model which are among the factors that will affect the choice of MLH location. Further, qualitative factors were also selected to determine the order of establishment of selected MLHs which include: (1) availability of open spaces for establishing MLH, (2) proximity to the airport, (3) the level of safety in the selected site, (4) the availability of utility infrastructure in prospective locations, (5) availability of labor, (6) proximity to disaster vulnerable districts, (7) support from local government, and (8) proximity to the armed police force disaster management.
Source: World Food Programme