Search Results for "particle swarm optimization algorithm java code"
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6 programs for "particle swarm optimization algorithm java code" with 2 filters applied:
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TEESer
Tool for Engineering Emergent Selforganizing bEhavioR
... 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. -
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Solid Python
A comprehensive gradient-free optimization framework written in Python
Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them. -
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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... -
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MOEA Framework
A Free and Open Source Java Framework for Multiobjective Optimization
The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. In addition, the MOEA... -
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Search Agents - a framework for collaboration of meta-heuristic agents
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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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