Welcome to ORDECSYS applications

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GASDECSYS: A Decision Support System for Gas Distribution Networks

GASDECSYS is a decision support tool for the design of gas transmission networks and the management of their operations. It simulates flows and pressures, computes least cost designs and optimal supply policies. Its fast responses make it a perfect tool to explore the variety of operating conditions due to seasonal and stochastic variations of the demands.

GASDECSYS is based on powerful and innovative techniques to solve the complex and nonlinear models of gas transmission networks.

ETEM: A strategic assessment tool for energetic and environmental policy

ETEM is a bottom-up model that finds optimal energy and technology based decisions taking into account the energy needs of a city or a region. The model aims at finding an energy mix with minimal cost, investing in equipment (new technology), production capacity (installed technology) and import/export of primary or secondary energy. The model permits an assessment of energy and environmental policies, measures emissions due to the energy system and finds optimal ways to satisfy constraint on the emissions.

DET2STO: A modeling tool

DET2STO is a tool that transforms a stochastic version of a model written in AMPL or in GNU MathProg into a deterministic equivalent in a fully automated way.

It outputs a model file and a data file that can be then processed by the algebraic modeling language AMPL and optimized by a solver.

NeatWork

NeatWork is a free program specifically fashioned for the design of entirely gravity-driven water distribution networks for rural areas.

This program is developed by the NGO APLV (Agua Para La Vida) and ORDECSYS. Mosek Solver is graciously made available for the optimisation part of the software.

OBOE: Oracle-based Optimization Engine

OBOE is an open source software for general convex optimization. It assumes that a user-made code, thereafter named oracle, is capable of delivering first order information on the key elements of the problem (support the feasible set, support to the objective function). The engine exploits this information to construct the so-called localization set which is a polyhedral approximation of the set of optimal solutions.