Cruz Cantillo, Yesenia

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    Integrating complex evacuation dynamics in resource allocation for relief operations
    (2008) Cruz Cantillo, Yesenia; Medina Borja, Alexandra; College of Engineering; Rullán Toro, Agustín; Triantis, Konstantinos P.; Department of Industrial Engineering; Valdes, Didier
    The dynamic framework created as part of this research work –named the “Service Quality Response Cycle” (SQRC) Model– was formulated to understand the complex multi-factor dynamic processes evolving over time during a hurricane emergency. SQRC maps the process of interdependence between resource allocation and human service satisfaction and hypothesizes key mechanisms governing this relationship. Exogenous factors such as customer reactions to the category event; training level of response personnel; race, social stratum, home/pet ownership and education are all taken into account. Satisfaction and demographic data was collected from victims of the 2005 Katrina Hurricane and paired with real operational data. The model was then calibrated/validated by data from the 2005 Rita Hurricane. Findings suggest that in order to maintain an acceptable level of satisfaction more attention could be given to the reduction of training time of relief workers. Variations in the system that would affect negatively the level of satisfaction are related to a reduction in the provision of meals. Financial assistance and mental health care are not sensitive to independent variation.
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    Dynamic transportation and humanitarian logistics model: a decision support tool to forecast and prioritize critical supplies distribution during emergency relief operations
    (2013) Cruz Cantillo, Yesenia; Valdés Díaz, Didier M.; College of Engineering; Holguín Veras, José; Cruzado Vélez, Ivette; Perdomo, José L.; Department of Civil Engineering; Cancelos, Silvina
    The optimal mobilization of materials, personnel and relief supplies to a disaster site could be the difference between life and death for the affected population. The purpose of this dissertation is to develop a system dynamics model for the forecasting, prioritization and distribution of critical supplies during relief operations in case of a hurricane event, integrating GIS information. Data obtained come from operational reports of agencies involved in the relief operation during Hurricane Georges, such as: PRDOH, Puerto Rico National Guard, Civil Defense State Agency of Puerto Rico, PRDOTP and PRHTA, along with reports from the U.S. Army Corps of Engineers and FEMA and flooding maps from the Puerto Rico Planning Board and FEMA. Visual field inspections of the road network in the western area and interviews with locals were conducted in order to gather information about travel times, roadway classifications and geometric characteristics of the roads as well as the location of distribution centers, shelters, points of distribution and kitchens facilities. Information about logistics was collected during telephone interviews and visits with officials of the PRDOE, PREMA, PRDOH, Emergency Management Office, Municipal Emergency Management Office and the School Food Authority. Travel times studies were conducted to corroborate travel times outputs generated via TransCAD. Eight road networks were built for the analysis of vehicle routing procedure. Then, alternate routes were delineated and outputs of these analyses were incorporated as inputs into the system dynamic model. The model was built using the Stella® software and the vehicle routing procedures were run using TransCAD® software. This system dynamics model is circumscribed as part of a methodological framework for real time data collection during a disaster. The model allowed to establish the people’s decision and transportation characteristics that determine the timing of evacuation; to simulate the behavior of key variables making a relation between level of hazard and people decision to evacuate; to estimate for each level of natural hazard, the time frequency to order and the order size of each relief supply to be needed in shelters and point of distribution; and to reveal which routes cause more delays during distribution of relief supplies.