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Gosl is a Go library to develop Artificial Intelligence and High-Performance Scientific Computations. The library tries to be as general and easy as possible. Gosl considers the use of both Go concurrency routines and parallel computing using the message passing interface (MPI). Gosl has several modules (sub-packages) for a variety of tasks in scientific computing, image analysis, and data post-processing.

scientific-computing visualization linear-algebra differential-equations sparse-systems plotting mkl parallel-computations computational-geometry graph-theory tensor-algebra fast-fourier-transform eigenvalues eigenvectors hacktoberfest machine-learning artificial-intelligence optimization optimization-algorithms linear-programmingAn incremental linear constraint-solving algorithm (Auto Layout) in Swift.

cassowary algorithm simplex constraint-solver auto-layout linear-programming dslBLT is a C/C++ library for solving certain integer linear programming (ILP) problems using techniques that come from the theory of lattices. It is complementary to many existing, traditional ILP solvers in that there are problems it solves very well and very quickly which traditional solvers do not (and vice-versa). For a theoretical discussion, see our conference paper from the 2015 SMT Workshop.

linear-programming decision-procedure lattice-reduction haskell haskell-bindings solver ilp ilp-solver haskell-api yices glpk ntlOMPR (Optimization Modelling Package) is a DSL to model and solve Mixed Integer Linear Programs. It is inspired by the excellent Jump project in Julia. The Wikipedia article gives a good starting point if you would like to learn more about the topic.

integer-programming linear-programming r mip milpThis is a Rust implementation of the Cassowary constraint solving algorithm (Badros et. al 2001). It is based heavily on the implementation for C++ at nucleic/kiwi. The implementation does however differ in some details. Cassowary is designed for solving constraints to lay out user interfaces. Constraints typically take the form "this button must line up with this text box", or "this box should try to be 3 times the size of this other box". Its most popular incarnation by far is in Apple's Autolayout system for Mac OS X and iOS user interfaces. UI libraries using the Cassowary algorithm manage to achieve a much more natural approach to specifying UI layouts than traditional approaches like those found in HTML.

cassowary linear-programming layout gui constraint-solverurbs is a linear programming optimisation model for capacity expansion planning and unit commitment for distributed energy systems. Its name, latin for city, stems from its origin as a model for optimisation for urban energy systems. Since then, it has been adapted to multiple scales from neighbourhoods to continents. There are 2 ways to get all required packages under Windows. I recommend using the Python distribution Anaconda. If you don't want to use it or already have an existing Python (version 3.5 recommended, 2.7 is supported as well) installation, you can also download the required packages by yourself..

pyomo pandas optimisation-model mathematical-modelling linear-programming energy-systemOptimus is a library for Linear and Quadratic mathematical optimization written in Scala programming language. This program comes with ABSOLUTELY NO WARRANTY. This is free software, and you are welcome to redistribute it under certain conditions; See the GNU Lesser General Public License v3 for more details.

algebra optimization linear-programming quadratic-programming integer-programmingMaps can be displayed in pyNMS to draw all network devices at their exact location (longitude and latitude), using the mercator or azimuthal orthographic projections. Networks can be exported as a .KML file to be displayed on Google Earth, with the same icons and link colors as in pyNMS.

network automation graph-visualization linear-programming network-gis-visualization network-visualization network-programming network-automation napalm jinja2 netmiko yaml cisco juniper pyqt network-engineering networkingpyTSP uses various approaches to solve the TSP (linear programming, construction heuristics, optimization heuristics, genetic algorithm). It provides a geographical step-by-step visualization of each of these algorithms.

travelling-salesman-problem genetic-algorithm heuristics flask flask-socketio linear-programming genetic-algorithms gis webgl algorithm-visualisation leafletjs openstreetmap 3d-visualizationIn optical networks, the Wavelength Divison Multiplexing (WDM) technology is used to increase the capacity of fibers to transmit information, by splitting a beam of light into different wavelengths, which travel simultaneously. In an all-optical network, a wavelength can cross an optical switch without Optical-Electrical-Optical (OEO) conversion. While this is a step forward towards cheaper and "greener" networks, a trade-off is that there has to be an end-to-end "wavelength continuity": a wavelength stays the same from the source edge to the destination edge, and it cannot be used by different lightpaths on the same optical fiber.

optical-network wavelength-division-multiplexing metaheuristics linear-programming gis geovisualization leaflet cvxopt flask sqlalchemy graph-algorithms wdm wavelength graph-coloring wavelength-assignment graph-transformation nodemaxcovr was created to make it easy for a non expert to correctly solve the maximum covering location problem described by Church. Implementations of this problem (such as optimimum AED placement) may use commercial software such as AMPL, Gurobi, or CPLEX, which require an expensive license, or use open source licenses but not provide source code to the analysis performed (e.g., Bonnet 2014) This builds a substantial barrier to implement and reproduce these analyses. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

r linear-programming distanceLinear Programming Diet Experiments

linear-programming operations-research mathematics optimization healthy-dietsThis is a Common Lisp library for solving linear programming problems. It is implemented in pure Common Lisp, instead of calling a high performance library. This has the advantage of being dependent on only a couple community standard libraries (ASDF, Alexandria, Iterate). However, this limits the performance of solving larger problems. If there is interest in a high performance backend, let me know; it shouldn't be hard to make the backend modular. The linear-programming library is avalible in both the main Quicklisp distribution and Ultralisp, so it can loaded with with (ql:quickload :linear-programming). You can check that it works by running (asdf:test-system :linear-programming).

common-lisp linear-programming
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