Enhancing Humanitarian Logistics and the Transportation of Relief Supplies: Integrating System Dynamics and Vehicle Routing

Enhancing Humanitarian Logistics and the Transportation of Relief Supplies: Integrating System Dynamics and Vehicle Routing

Yesenia Cruz-Cantillo (University of Puerto Rico – Mayagüez, Puerto Rico) and Carlos González-Oquendo (University of Puerto Rico – Mayagüez, Puerto Rico)
Copyright: © 2018 |Pages: 34
DOI: 10.4018/978-1-5225-4077-9.ch016


This chapter describes a system dynamics model developed for forecasting, prioritization, and distribution of critical supplies during relief operations in case of a hurricane event, while integrating GIS information. Development of alternates' routes selection through vehicle routing procedures and the results incorporation into this system dynamics model allows decisions about the operation in case of a major catastrophe and any preparation for future events. The model developed is also able to (1) establish people's decision and transportation characteristics that determine evacuation time; (2) simulate the behavior of key variables due to the relation between hazard level and people's decision to evacuate; (3) estimate for each natural hazard level the time frequency to order and the order size of each relief supply to be needed in shelters and points of distribution; and (4) reveal which routes cause more delays during relief supplies distribution.
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System Dynamics

The basis of system dynamics is to consider all “things” as a whole and comprehend how all the objects in the system interact with one another. The interactions between objects and people occurs through feedback loops, therefore, a change in one variable, influences other variables over time, and in turn impacts the original variable and so on (Forrester, 1961). System dynamics is interdisciplinary, and it is discussed in the theory of nonlinear dynamics and feedback control systems built on mathematics, physics, and engineering (Sterman, 2001). The understanding of the basic structure of a system, and the understanding of this behavior that it can generate is what system dynamics attempts to do (Azar, 2012).

System dynamics has been also employed in modelling distribution complex systems. Such is the case of modelling a newer healthcare supply network causal loop diagram where authors analyzed and predicted the growth pattern of a healthcare logistic network (Battini et al., 2013). The use of system dynamics can also be extended to mobile broadband market where authors modeled the dynamic behavior of wireless ecosystem (Thakker et al., 2013). And the dynamics of social care workforce could be comprehended through system dynamics through the identification of the key feedback loops and their use to analyze the adult social care system (Onggo, 2012). Other applications of system dynamics include: monitoring phases of new product development process (González et al., 2014), sustainable food security based on initiatives exclusive to the farmers (Oyo et al., 2016), and analyze daily calorie intake of the population in Ethiopia (Ayenew, 2015) among others.

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