COIN-OR
The Computational Infrastructure for Operations Research (COIN-OR**, or simply COIN) project is an initiative to spur the development of open-source software for the operations research community. Why open source? The Open Source Initiative explains it well. When people can read, redistribute, and modify the source code, software evolves. People improve it, people adapt it, people fix bugs. The results of open-source development have been remarkable. Community-based efforts to develop software under open-source licenses have produced high-quality, high-performance code---code on which much of the Internet is run. Why for OR? Consider the following scenario. You read about an optimization algorithm in the literature and you get an idea on how to improve it. Today, testing your new idea typically requires re-implementing (and re-debugging and re-testing) the original algorithm. Often, clever implementation details aren’t published. It can be difficult to replicate reported performance. Now imagine the scenario if the original algorithm was publicly available in a community repository. Weeks of re-implementing would no longer be required. You would simply check out a copy of it for yourself and modify it. Imagine the productivity gains from software reuse!
Keywords for this software
References in zbMATH (referenced in 66 articles )
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Sorted by year (- D’Ambrosio, Claudia; Vu, Ky; Lavor, Carlile; Liberti, Leo; Maculan, Nelson: New error measures and methods for realizing protein graphs from distance data (2017)
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- Escudero, Laureano F.; Garín, María Araceli; Unzueta, Aitziber: Cluster Lagrangean decomposition in multistage stochastic optimization (2016)
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- Lejeune, Miguel A.; Margot, François: Solving chance-constrained optimization problems with stochastic quadratic inequalities (2016)
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- Santos, Haroldo G.; Toffolo, Túlio A.M.; Gomes, Rafael A.M.; Ribas, Sabir: Integer programming techniques for the nurse rostering problem (2016)
- Berthold, Timo; Hendel, Gregor: Shift-and-propagate (2015)
- Brito, Samuel Souza; Santos, Haroldo Gambini; Poggi, Marcus: A computational study of conflict graphs and aggressive cut separation in integer programming (2015)
- Huang, Kuo-Ling; Mehrotra, Sanjay: An empirical evaluation of a walk-relax-round heuristic for mixed integer convex programs (2015)
- Mason, Luke R.; Mak-Hau, Vicky H.; Ernst, Andreas T.: A parallel optimisation approach for the realisation problem in intensity modulated radiotherapy treatment planning (2015)
- Omer, Jérémy; Towhidi, Mehdi; Soumis, François: The positive edge pricing rule for the dual simplex (2015)
- Berthold, Timo: RENS. The optimal rounding (2014)
- Digne, Julie; Cohen-Steiner, David; Alliez, Pierre; De Goes, Fernando; Desbrun, Mathieu: Feature-preserving surface reconstruction and simplification from defect-laden point sets (2014) ioport
- Towhidi, Mehdi; Desrosiers, Jacques; Soumis, François: The positive edge criterion within COIN-OR’s CLP (2014)
- Aldasoro, Unai; Escudero, Laureano F.; Merino, María; Pérez, Gloria: An algorithmic framework for solving large-scale multistage stochastic mixed 0-1 problems with nonsymmetric scenario trees. II: Parallelization (2013)
- Balas, Egon; Qualizza, Andrea: Intersection cuts from multiple rows: a disjunctive programming approach (2013)
- Belotti, Pietro: Bound reduction using pairs of linear inequalities (2013)
- Berthold, Timo: Measuring the impact of primal heuristics (2013)