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

Effective resource allocation and quantification of its benefits are essential in practical engineering problems. However, determining the allocation and location of resources is computationally challenging when dealing with large, interconnected systems, as is the case of infrastructure networks. We address the allocation and location of different types of resources to a set of potential sites in an infrastructure system, aiming to satisfy service demands at a minimum cost (e.g., in the context of disaster preparedness). Exact optimization methods become impractical for realistic network sizes, whereas fully heuristic approaches lack optimality guarantees. We use exact optimization to solve a heuristically pre-processed version of the resource location/allocation problem, which incorporates constraints that capture topological network properties based on community detection algorithms. Adding topological constraints leads to significant reductions in computation time without considerable deviation from optimal solutions, as community detection mostly forbids solutions that are unattractive in terms of network topology. The proposed approach to resource allocation incorporates a novel way to account for infrastructure network configurations within linear programming, leading to computational efficiency while producing solutions that capture the inherent topological properties of the network.

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

Resilience of infrastructure networks is key for urban development, mostly when understood as the way in which physical systems help societies prosper. In this sense, infrastructure engineering must incorporate the societal aspects related to infrastructure operation, namely: the organizations involved in infrastructure operation (government, agencies, contractors, regulators), and the general public who uses and benefits from these systems. The explicit consideration of these parties impacts the modeling and analysis of infrastructure systems with regards to how decisions are made (depending on the type of stakeholder, and its organizational constraints) and how the impact is measured (depending who the constituents are). For example, in the context of risk assessment and management, organizational constraints may imply stakeholders with divergent interests, or centralized vs. decentralized resource availability, decision processes, and operations, etc.; regarding user-related aspects, socio-economic vulnerability may have an impact on how different segments of the population experience the (lack of) service/benefits of an infrastructure system. Incorporating these aspects may affect the definition of performance metrics of interest and, consequently, influence risk management policies. In this project, we propose recovery strategies for interdependent networks of power, gas, and water in Shelby County, TN (USA), considering operators’ as well as societal objectives within an optimization framework.

Contact: Camilo Gomez

• jMDP (by G. Riaño)
  A java package to solve general discrete dynamic programming problems. Part of the jMarkov project
• RoutePlotter (by Jorge E. Mendoza)
  MS Excel add-in for visualization and analysis of vehicle routes. Keywords: vehicle routing problem; VRP; DSS
• jCW (by Jorge E. Mendoza, Christelle Guéret, Andrés L. Medaglia, Nubia Velasco & Juan Villegas)
  Object-oriented framework for the rapid development of savings-based heuristics for vehicle routing
• jSplit (by Juan G. Villegas, Andrés L. Medaglia, Christian Prins, Caroline Prodhon, and Nubia Velasco)
  Split-based (route first, cluster second) framework for vehicle routing
• jPulse (by Leonardo Lozano and Daniel Duque)
  This is the Java implementation of the pulse algorithm as published in: “Lozano, L. and Medaglia, A. L. (2013). On an exact method for the constrained shortest path problem. Computers & Operations Research. 40 (1):378-384.”

• JGA and MO-JGA (by A. Medaglia and E. Gutiérrez)
  A java framework for single and multiobjective evolutionary programming.

• jMarkov (by G. Riaño and others)
  A java package to model and solve Markov processes, Markov Decision Processes and QBDs.
• Central Limit Theorem (XL-CLT) (by G. Riaño)
  This program shows the Central Limit at work.
• MarkovExcel (by G. Riaño)
  This program is used for steady state and transient analysis of discrete and continuous Markov Chains.
• XL-Inventory (by G. Riaño)
  This programm is used for analysis of various stochastic inventory models.
• Markovi (by G. Riaño)Didactic applications that simulates the behavior of discrete time Markov Chains (in Spanish).

• Syncro (by G. Riaño)
  Allows you to synchronize two folders (and sub folders)
• LaTex
  • Manuals/Guides/Tutorials
    • Manual de Instalación de LaTeX
      Instrucciones para Instalar Winedt, Latex y compañía en castellano (in Spanish).
  • Classes
    • Clase Uniandes-tesis (G. Riaño, N.Santamaría)
      Esta clase permite elaborar fácilmente tesis que cumplen con los requerimentos de presentación de la Biblioteca de Uniandes (in Spanish).
  • Software
    • LaTeXcel(by G. Riaño)
      Convert an Excel table to latex with a single click! (borders and all). Convert an Excel table to latex with a single click! (Borders and all). To install it, save this file in any folder, open  excel, and add it through the menu tools/addins. This program is based on excel2latex by Joachin Marder.
    • PicLatex(by G. Riaño)
      Generate graphics for LaTeX from your Power Point presentation. If you are good using the drawing capabilities of Power Point, and want to use it to generate the graphics for a Latex document this is the program for you. Probably somebody told you that you can save a Power Point presentation in wmf format and then use wmf2eps to convert them to eps and then pdftolatex to convert them to pdf (if you want to use pdfLatex). The process is long and cumbersome, and if you want to change something in the graph you have to repeat it. ouch! This program calls all those applications for you, so you convert all the slides (or a single slide)  to eps and pdf with a single click!
      To install just save the add-in in the hard drive. Then open  Power Point presentation, and add the add-in via the menu Tools/Add Ins. You MUST install wmf2eps first and make sure it works on it own! Wfm2eps can be downloaded here.

• ImageParty (by L.Lozano)
  Allows you to convert images into .csv tables with the RGB information for each pixel and backwards.
• Coin OR (by V. Pillac)
  • CoinOR LiveCD (1)
    A Ubuntu based Live CD with Python 2.6 and some of the main CoinOR libraries pre-installed
  • CoinOR Live CD with Gurobi 2 & 3 (3)
    Same as above, with Gurobi 2.0.3 and 3.0.1 pre-installed
  • CoinOR installation script
    A script that will install the software packaged in the Live CD for Ubuntu and other Debian based Linux distributions.

  See this page for more information.

• • jSplit v.2008.11.08 (exe file) (beta)