Search Results for "optimization"
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31 projects for "optimization" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
...It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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The Algorithms Python
All Algorithms implemented in Python
...It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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ngraph.path
Path finding in a graph
...It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. ... -
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FRODO 2
Open-Source Framework for Distributed Constraint Optimization (DCOP)
FRODO is a Java platform to solve Distributed Constraint Satisfaction Problems (DisCSPs) and Optimization Problems (DCOPs). It provides implementations for a variety of algorithms, including DPOP (and its variants), ADOPT, SynchBB, DSA... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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C++ Library of Abstract Algebra concepts and arithmetic algorithms defined in terms of these concepts, using Instigate Generic Programming Methodology. Based on this library we plan to develop Linear Algebra and Optimization concepts and algorithms.
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Evolutionary Algorithm
Evolutionary Algorithm using Python
...Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts. -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer -
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TEESer
Tool for Engineering Emergent Selforganizing bEhavioR
...Designers can continue to use their domain tools such as favorable simulator and by pluging it into the framework can take advantage of distributed simulations in the grid, various analyzers, optimizers (particle swarm optimization, genetic algorithms, ...). See Wiki pages for more information. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. ... -
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NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
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JBernstein
JBernstein: Exploration techniques for non-linear constraint checking
...It is mainly used in the verification or synthesis of cyber-physical systems where the system model is nonlinear. The tool also supports specifications in assume-guarantee style. The underlying algorithm is based on a translation to Bernstein polynomials, and several optimization techniques are implemented to ensure efficiency. Concerning performance, the tool enables to check all examples in the PVS Bernstein testsuite within a second, which can be an order of magnitude faster than some other tools such as QEPCAD or REDLOG. Although JBernstein uses double, it offers automatic error-estimation capabilities (experimental) so that the generated result is correct (the solver may return unknown when the error-estimate is too large) -
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SEO & SEM - Marketing Text Writer
Open Source SEO & SEM Text Creation Tools for free Article Writer
Open Source Tool for Search Engine Optimization (SEO & SEM) used for automatic content processing. These SEO Content Genrators and Article Writers based on Text Writer: https://www.artikelschreiber.com/en/ https://www.unaique.net/en/ https://www.unaique.com/ https://www.artikelschreiben.com/ https://www.buzzerstar.com/ https://googleduplicatecontentsolver.sourceforge.io/ https://inkassos.github.io/inkasso/ https://www.artikelschreiber.com/opensource/ https://www.sebastianenger.com/ https://www.artikelschreiber.com/marketing/review/ https://muckrack.com/markus-muller https://linktr.ee/textgenerator Code Contains: - Perl Source code, language databases and more -
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Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.
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Java Combinatorial Optimization Platform is used to solve combinatorial problems using common interface, providing means to easily add new algorithms and problems and to benchmark them.
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Semantic query optimization (SQO) is the process of finding equivalent rewritings of an input query given constraints that hold in a database instance. We present a Chase & Backchase (C&B) algorithm strategy that generalizes and improves on well-known methods in the field. The implementation of our approach, the pegasus system, outperforms existing C&B systems an average by two orders of magnitude.
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Search Agents - a framework for collaboration of meta-heuristic agents
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LSGTL means LLX’s Static Graph Template Library which is a light-weighted header-only template library developed mainly for static graph analysis. LSGTL is expected to be used in laboratories for research purposes mostly.
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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Combean is a Java framework for mathematical structures and optimization algorithms. Through a set of Java interfaces and JavaBeans-based config, Combean glues optimization codes together - leading to more interoperable, adaptable and flexible solutions.
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The Flexible Registration and Evaluation Engine (f.r.e.e.) allows the composition, evaluation and optimization of image processing/registration algorithms. It also aims to boost the exchangeability and comparability of data and algorithms in research.
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The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
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An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.
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This project provides some hyperheuristics, implemented as C libraries. A hyperheuristic can be used to handle any optimization problem, as long as you implement some simple specific code to interact with it. Some examples/applications are also provided.
