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

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.

Rainwater harvesting is the process of collecting, storing, and distributing rainwater for reuse, rather than allowing it to run off. Greywater recycling consists of purifying processes that remove contaminants present in wastewater coming from faucets, showers, baths, clothes washing, and dishwashing, so that it can be reused, instead of becoming inlet wastewater for municipal wastewater treatment plants. In urban areas, rainwater harvesting and greywater recycling systems provide additional water supplies for houses, buildings, and industries, and also help to mitigate flooding events and pollution. Construction companies are looking for eco-friendly systems that benefit the environment while being profitable. This paper proposes a decision support system (DSS) for the design of rainwater harvesting and greywater recycling system (RHGRS) in residential construction projects. The DSS uses optimization to support construction companies in the design of a RHGRS that minimizes construction and operational costs. With the underlying optimization routine, the DSS addresses both the challenges of deciding whether to construct or not a RHGRS for a residential unit and its minimum-cost design. It is expected that the DSS will help construction companies to make decisions toward sustainable and eco-friendly cities.

Contact: Andres Medaglia

Increasing urbanization is an undeniable feature of this century. Addressing urban growth under severely constrained resources is a task that demands comprehensive efforts in planning towards efficient development: optimizing the treatment of resources (natural, economic) and residues (emissions, waste, idle time), for which an accurate understanding of urban processes is necessary. While network analysis and systems dynamics provide tools to describe and understand relationships within and between stakeholders and the physical world, statistical models and simulation allow to estimate and predict behavior patterns that enable better decision making. Qualitative and quantitative descriptions of urban problems are translated to optimization models that provide support in the design of public policy and strategic planning in problems such as: land-use regulation; incentives and planning for renewable energy adoption; configuration and planning for transportation systems; resource allocation for disaster preparedness.

Contact: Camilo Gomez

In the context of infrastructure resilience, key decisions occur in the aftermath of adverse events, but most importantly, preemptive decisions must be made without knowledge about the characteristics of a potential future event. An optimization framework is proposed to address problems in which preemptive decisions are coupled with those eventually required to respond to an uncertain adverse event. Strategic decisions are pursued regarding whether to proactively retrofit or reactively repair bridges in a transportation network under seismic hazards, aiming to minimize the cost of maintaining travel times under a set of adverse scenarios. A two-stage stochastic programming approach is proposed, which relates pre- and post-event decisions, using a decomposition of the optimization problem which is advantageous when dealing with complex networks. We perform an analysis of the San Francisco Bay Area transportation network, as an instance of a realistic, complex infrastructure network. Results evidence the potential of the approach to provide risk-informed decision support, while being able to deal with large sets of components and scenarios under an exact optimization approach, and solving problems with millions of variables and constraints.

Contact: Camilo Gomez