Search Results for "parallel genetic algorithm"
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Showing 4 open source projects for "parallel genetic algorithm"
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MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
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PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. -
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PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.
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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.
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Remote Network Monitoring and Management for an IoT WorldDomotz is the premier Remote Network Monitoring and Management platform for IoT. We offer powerful network management software for MSP's, Integrators, Security Professionals, and Business Owners. Domotz enables the complete solution to cost-effectively manage and monitor your customers’ networks with plug and play setup, a friendly UX, and a comprehensive feature set, accessible from any desktop browser or mobile device. Utilize one interface to manage multiple networks at multiple locations anywhere in the World. One person can deploy remote monitoring and management in less than 15 minutes.
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