Search Results for "swarm"

Integrated component-based and cellular automata (CA) Parallel DEVS simulator: https://acims.asu.edu/devs-suite/ OFFERS: 1) synchronized execution & animation, 2) run-time linear/superdense I/O & state trajectories, 3) Action Level Real-Time modeling & simulation, 4) model checking, 5) ABM, 6) CA & composable CA playback, 7) KIB interaction modeling, 8) hierarchical model libraries, 9) Black-Box testing & debugging, 10) PostgreSQL repository, 11) FMU (OpenModelica), 12) OSATE (AADL)...

...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.

...Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. A fast parallel implementation of the network simplex method, and some full-fledged parallel/distributed MIP solvers will be added in the next version. ...

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. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process.

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 Framework provides the tools necessary to rapidly design, develop, execute and statistically test optimization algorithms.

This is a GUI, Java implementation of the Ant Colony Optimisation/Particle Swarm Optimisation (PSO/ACO2) rule induction algorithm. This project was inspired by Ant-Miner, but handles continuous attributes using PSO or now Differential Evolution.

As of 2012-12-18, this project may now be found at http://http://code.google.com/p/paba JECO is a Evolutionary Computation Library deveoloped in Java. It includes a variety of evolutionary optimization techniques such as genetic algorithm, genetic programming, evolutionary mapping methods, particle swarm optimization, ant colonies, etc.

Swarm framework for chemicals, to neurons, to group models and species models and etc. I will try to keep one version of the code independent of any platforms, but I will also be integrating the code with JADE, JBoss and my software.

A particle swarm optimization demo written by students in the digital communication msc program (2010) at uni-kiel.

A demonstration of the result of using an agent based approach in software. Shows a swarm of icons representing agents that follow user selected rules.

CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.

JSwarn is a particle swarm optimization (PSO) package written in Java. Designed to require minimum effort to use (out of the box) while also highly modular.

JGenAlg is a java toolbox for working with metaheuristic procedures (Genetic Algorithms, Island model, Particle Swarm, Ant Swarm). JGenAlg have a GUI, a Client/Server architecture, work with threads and can be use under distributed enviroments.

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.

Particle Swarm Optimization toolkit (with GUI) - Allows you to implement PSO algorithm for optimization of engineering/finance/management systems.