Analytics-based solutions for healthy and sustainable cities
In an era where people health has been unjustly impacted by their income, age, gender, education, ethnicity, and socioeconomic status, programs like the Recreovía and the Ciclovía Recreativa serve the entire community regardless of any of these factors with a health-focused approach. Accordingly, the necessity to bring healthy living into people’s daily lives has been and will continue to be a significant challenge for public health practitioners and city officials. This challenge inevitably involves assigning resources innovatively and efficiently using analytics-based techniques towards the goal of having healthier and sustainable cities.
See the video of the RecreoBOG project
|
|
Contact: Andrés L. Medaglia
Related work and links:
- EpiAndes research group at Universidad de los Andes.
- Medaglia, A. L. (2017). Promoting health and wellness through OR. In IFORS News. OR-Impact Section. 11(4). ISSN: 2223-4373
- IFORS Prize for Operations Research (OR) in Development (2017). 21th Conference of the International Federations of Operational Research Societies (IFORS). Quebec City (Canada) .
- Abolghasem, S., Solano, F., Bedoya, C. D., Navas, L.P., Ríos. A. P., Pinzón. E. A., Medaglia, A. L., Sarmiento, O. L. (2018). A robust DEA-centric location-based decision support system for expanding Recreovía hubs in the city of Bogotá (Colombia). International Transactions in Operational Research.
- Abolghasem, S., Gómez-Sarmiento, J., Medaglia, A. L., Sarmiento, O. L., González, A. D., Díaz del Castillo, A., Rozo-Casas, Juan F., Jacoby, E. (2018). A Data Envelopment Analysis (DEA)-centric decision support system for evaluating Ciclovía-Recreativa (CR) programs in the Americas. Socio-Economic Planning Sciences. 61:90–101.
- Sefair, J. A., Molano, A., Medaglia, A. L., and Sarmiento, O. L. (2011). Locating neighborhood parks with a lexicographic multiobjective optimization method. In Community-Based Operations Research: Decision Modeling for Local Impact and Diverse Populations. Michael P. Johnson (Ed.). International Series in Operations Research & Management Science, Volume 167, Part 2, 143-171.
Public transportation systems: from demand estimation to route design
Bus rapid transit (BRT) systems such as TransMilenio (in Bogota) have become a real alternative to more expensive rail-based public transportation systems. However, once the BRT system infrastructure is operational, its success often depends on the routes offered to the population. One of the challenges that planners face is the estimation of the origin-destination (OD) matrix that is the key driver to the set of routes and frequencies that need to be offered to the population. This matrix captures how people move in the city from each origin to each destination throughout the day. The estimation of the OD matrix is challenged by the lack of complete information. In many BRT systems it is known where passengers board buses, but not where they leave the system. Based on a vast amount of (partial) data and the use of modern analytics techniques this research line is focused on estimating the OD matrix of public transportation systems. Once the OD matrix is estimated, the problem of finding a set of routes (services) and frequencies that minimizes the operational and passenger costs (travel time) while simultaneously satisfying the system’s technical constraints (e.g., demands for trips, bus frequencies, and lane capacities). Our approach to the problem is based on a mathematical formulation that exploits the underlying network structure. However, because of the vast number of routes, solving the problem directly is out of reach for most practical instances. Thus, our approach is based on decomposition strategies (e.g., simultaneous column-and-row generation and matheuristics) that break the problem into manageable parts.
|

Photo by mariordo59/ CC BY-SA 2.0
|
|
Contact: Andrés L. Medaglia
Related work::
- Walteros, J. L., Medaglia, A. L., and Riaño, G. (2015). Hybrid algorithm for route design on bus rapid transit systems. Transportation Science. 49(1):66-84.
- Feillet, D., Gendreau, M., Medaglia, A. L., Walteros, J. L. (2010). A note on branch-and-cut-and-price. Operations Research Letters. 38(5):346-353.
Modeling the evacuation dynamics under congestion
|
A key aspect related to network design, is estimating how a given system is going to perform under stress or an undesired event. We have worked on models that are able to evaluate the evacuation dynamics in a network of interconnected facilities (e.g., buildings). By using a macroscopic approach, a network optimization model determines the optimal evacuation paths under a rational behavior of the evacuees and without taking into account network congestion. Because this is overly optimistic, an (stochastic) microscopic approach incorporates congestion and the erratic behavior of the evacuees. By feeding back both models, a mesoscopic model is able to estimate evaluation times and identify bottlenecks that cause critical congestion during an evacuation. With this information, it is now possible to identify investment plans that make the network more robust and efficient in terms of disaster or shock.
|
Contact: Andrés L. Medaglia and Jorge A. Huertas
Building resilient and robust networks for efficient response
At a strategic level, optimizing the resilience of any given system requires optimizing decisions for diminishing vulnerability and increasing efficient response. We have worked on devising a comprehensive optimization framework that incorporates resilience and uncertainty of interconnected networks. The methodologies devised in this line of research help decision makers to plan where to invest in the networks (e.g., road network, supply chain, gas network, power network), so that after an uncertain and shocking (e.g., disaster or low-demand) event, the system is able to recover and perform well as early as possible.
|
 |
Contact: Andrés L. Medaglia
Related work:
González, A., Dueñas-Osorio, L., Sánchez-Silva, M., and Medaglia, A. L. (2016). The interdependent network design problem for optimal infrastructure system restoration. Computer-Aided Civil and Infrastructure Engineering. 31(5):334–350.