## 6 Experimental Tests  
### Case Study: Application of HCLP in Humanitarian Logistic Services  
According to the latest report of the Centre for Research on the Epidemiology of Disasters (CRED) [55], \"in 2019, at least 396 natural disasters were reported, killed 11,755 people, affected 95 million others and costing nearly 130 billion US dollars. Floods, storms and droughts accounted for almost 99% of the total number of affected people\". More importantly, the report indicates that \"the number of events in 2019 was slightly over the average of the last 10 years\". The highest priority in these kinds of situations is to help the survivors. Despite the unknown occurrence time and the place of the natural disasters, emergency preparedness and response activities should be conducted as pre-disaster and post-disaster actions. One of the applications of the proposed HCLP model is locating aid centers and module assignment that can improve the impact of strategic and tactical relief operations in humanitarian situations caused by disasters such as earthquakes, floods, storms, wars, medical epidemic emergencies, and droughts. According to the Disaster Operations Management (DOM) framework [56], disaster operations are usually categorized into four main phases as mitigation, preparedness, response, and recovery, as shown in Figure 3. The application of HCLP in the humanitarian facility location problem, in which the location of the capacitated aid centersis determined as a strategic decision, belongs to the preparedness activity phase. In the response phase, the assignment of the service providing units to the located aid centers with the objective of maximizing the covered demand of affected people is determined. From Figure 3, the decisions during mitigation and preparedness activities can be regarded as strategic decisions, the decisions during the response activity can be regarded as tactical decisions, and in the same way, the decisions during recovery phase are assumed as operational decisions. The gray filled part illustrates the domain of HCLP in humanitarian services, which includes the strategic and tactical decisions of preparedness and response phases. From an economical point of view, sitting relief facilities and equip them with whatever is necessary to provide services for all affected areas after an unknown disaster is not efficient and may be impossible. To overcome the uncertainty in time and place of the disasters and the scarcity of the resources, the problem of this case study is to determine the location of relief facilities in some public schoolyards, parks, parking lots, etc. with the aim of minimizing the number of facilities covering all demand points inside the coverage radius. The decisions of locating facilities are determined as a strategic preparedness activity before disasters happen, and when a disaster happens in any region, the government or any responsible organization can dispatch the limited modules (trucks, helicopters, medical services, mobile kitchens, shelter tents, etc.) to the located facilities to start service operations there. When the modules fulfill their operations, they can be dispatched to be assigned to the other facilities of other affected regions according to the demand requests. In this case study, it is supposed that, in each strategic period, one of the areas in South-Central (R1), North-Central (R2), and the Center (R3) of Japan are affected by a disaster requesting for services provided by the modules in tactical periods. Each tactical period is equivalent to one month, and each strategic period is composed of three tactical periods. The North-Central part (R2) can correspond to the Japan 2011 earthquake. The number of 160 points matching the cities with more than 150,000 inhabitants according to census results and the latest estimates [57] is considered as demand points and, also, as the potential locations for locating facilities. There are four kinds of modules with four possible sizes, three strategic periods each composed of three tactical periods.