Recent methods for sustainability analysis have involved the methodology of system dynamics for the representation of different landscape components that are analyzed. This document proposes a mathematical model based on system dynamics for the hydrological component in the sustainability analysis that includes the processes between precipitation and runoff. Additionally, the stability of the equilibrium point found with the theory of dynamic systems is studied. The modeling is carried out from a diagram of levels and flows, in order to obtain a system of ordinary differential equations of first order, linear, non smooth, that takes as state variables static and capillary storage, superficial storage, higher gravitational storage, lower gravitational storage (aquifer) and storage in the channel. The model was validated with time series of the Chinchina basin (Caldas, Colombia). From dynamical systems point of view, the system behavior has an equilibria point that depends on the saturation value in the static and capillary storage.
This document shows a model that seeks the sustainability of the Usable Solid Waste (USW) market in Bogotá, based on System Dynamics (SD), in order to understand the complex behavior of the phenomena that should be presented in this city market in the context of sustainability. Dynamic hypothesis suggests that two negative feedback structures exits, one that represents demand and another that represents supply and that interact under the assumption of free market with government intervention. Different strategies were modeled on both the demand side and the supply side to manage the system. As conclusion, the linear way in which the USW market currently develops is not adequate. It is necessary to institutionalize the market using the price so that it contributes to its sustainability and that both demand and supply are encouraged at the same time. Besides, district policy oriented to supply must be in accordance with the national policy that encourages demand to use more USW. Likewise, the internalization by all the actors of the market and applicability of the norm is required. The creation of public-private partnerships is required for the development of innovative projects in this area.
We present a hybrid algorithm based on Genetic Algorithms and Discrete Event Simulation that computes the algorithmic-optimal location of emergency resources. Parameters for the algorithm were obtained from computed historical statistics of the Bogotá Emergency Medical Services. Considerations taken into account are: (1) no more than a single resource is sent to an incident, (2) resources are selected according to incidentpriorities (3) distance from resource base to incident location is also considered for resource assignment and (4) all resources must be used equally. For every simulation, a different set of random incidents is generated so it’s possible to use the algorithm with an updated set of historical incidents. We found that the genetic algorithm converges so we can consider its solution as an optimal. With the algorithmic-optimal solution we found that arrival times are shorter than the historical ones. It’s also possible to compute the amount of required resources to reduce even more the arrival times. Since every Discrete Event Simulation takes a considerable amount of time the whole algorithm takes a heavy amount of time for large simulation time-periods and for many individuals for generation in the genetic algorithm, so an optimization approach is the next step in our research. Also, less restricted considerations must be taken into account for future developments in this topic.
The migration phenomena of human populations is a well-known issue in social, economic, and sociophysics studies. A common effect of non-forced migration is the fact that important cities gain population over the first years and become overpopulated. Therefore, neighboring cities receive all migration and end up geographically merging with the important ones. Several studies have addressed the social and economic reasons behind this effect, but a mathematical model has been lacking. Here, we construct a migration complex network with population and migration dynamics and carry out an indirect influences analysis of those dynamics. Using this, we can measure the effect of migration on population growth across cities. The results show that the analysis of the indirect influences reveals interesting facts about the mentioned migration effect and address the measurement of this. Given this, urban planners and city administrations can make use of these findings to improve their migratory research.
In this paper, we propose a hybrid optimization method to compute a reallocation of ambulances to obtain improved response times. As we want to minimize response times by changing ambulances allocations, we develop a hybrid algorithm based on a genetic algorithm, with randomized ambulances configurations as population individuals. Also, we embed into the genetic algorithm discrete event simulations to model the reporting, assignment, travel, and attendance processes. We later find that the algorithm optimizes the response times for simulated events, even though these times don’t yet compare to response times found in real data. So, we need to evaluate any improvement in real response times. As a study case, we use data from 2014 to 2017 provided by the health authority of Bogotá, Colombia, that contains real values of emergency medical incidents, and the quantity and type of ambulances that attended such incidents.
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