Medaglia, A. L., Lozano, L., Duque, D. (2018). Solving hard shortest path problems with the pulse framework. In IFORS News. Tutorial Section. 12(2). Available at: http://ifors.org/newsletter/ifors-news-june-2018.pdf

Medaglia, A. L., Uribe, C. M. (2019). . Capiro: La Ingeniería de las Flores. Revista de Ingeniería. 47:68-75. Available at: https://ojsrevistaing.uniandes.edu.co/ojs/index.php/revista/article/view/979

Huertas, J. A., Duque, D., Segura, E., Akhavan-Tabatabaei, R., Medaglia, A. L. (2019). Evacuation dynamics: a modeling and visualization framework. OR Spectrum. Available at: https://doi.org/10.1007/s00291-019-00548-x

Fontecha, J. E., Duque, D., Guaje, O. O., Akhavan-Tabatabaei, R., Rodríguez, J. P., Medaglia, A. L. (2019). Combined maintenance and routing optimization for large-scale sewage cleaning. Annals of Operations Research. Available at: https://doi.org/10.1007/s10479-019-03342-8

Sefair, J. A., Espinosa, M., Behrentz, E. & Medaglia, A. L. (2019). Optimization model for urban air quality policy design: A case study in Latin America. Computers, Environment and Urban Systems. 78. Available at: https://doi.org/10.1016/j.compenvurbsys.2019.101385

Zambrano, J. A., Huertas, J. A., Segura-Durán, E., Medaglia, A. L. (2019). Time estimation and hotspot detection in the evacuation of a complex of buildings: a mesoscopic approach and case study. IEEE Transactions on Engineering Management. Available at: https://doi.org/10.1109/TEM.2019.2960354

Duque, D., Medaglia, A. (2019). An exact method for a class of robust shortest path problems with scenarios. Networks. Available at: https://doi.org/10.1002/net.21909

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.

Oil palm agricultural systems involve large extensions of land that demand careful planning of the harvesting operations. The plantation manager is in charge of synchronizing resources (i.e., crews and a complex cableway network) to harvest at the right time to maximize palm oil yield in latter stages of the value chain. In particular, in this type of crop it is ideal to visit each palm every eight to ten days to avoid loose fruit picking, over-ripeness, or rotten fruit harvesting. To optimize harvest operations, we propose an end-to-end analytics solution involving data treatment, predictive, and prescriptive models (optimization and simulation) in this agricultural system. At the core of our approach lies a set of interconnected models that use optimization, heuristic techniques, and simulation. These models cover strategic (harvest cycle), tactical (resource allocation), and operational (transport allocation) decisions. The results show a strong potential for improving yield by adjusting the harvest cycle length from 19.6 to 8.3 days in a 2000-hectare plantation located in the Colombian Orinoquia. This is a joint research collaboration with the Centro de Estudios de la Orinoqia (CEO).

Contact: Andrés L. Medaglia

The microstructure of pure Copper processed by machining manufacturing process such as turning and milling is explored with the aim to create highly refined grain structures to achieve the highest strength while postponing the potential possibilities for future recrystallization which inherently lead to non-thermally-stable materials. These two targeted properties are often conflicting requirements: an improvement in one (strength) generally leads to a deterioration in the other (thermal stability). Hence, it is not straight forward to follow a procedure that would set both the properties at their individual best: all that can be achieved is a tradeoff, a compromise between the two objectives. Here we attempt to obtain a set of optimum solutions using multi-objective optimization algorithms as well as the Kuhn-Tucker optimality conditions. Additionally, we verify the solution empirically by creating the sample condition. The resulting microstructure is characterized via electron microscopy confirming the theoretical result. The thermal stability of the optimal solution is verified as well. Finally, we studied the kinetics of crystallization on the optimal solution using the Johson–Mehl–Avrami–Kolmogorov (JMAK) theory.

Contact: Sepideh Abolghasem