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JCOOL is an open-source Java library for continuous optimization. It implements both numerical and nature-inspired algorithms. We have included a huge set of benchmarking problems and a GUI tool with various visualizations.
Quickstart documentation can be found here.
Methods and benchmarking problems are described in Vladimír Bičík's Master's Thesis.
Note: some of the methods from other packages are adapted to our interfaces.
- AACA (Adaptive Ant Colony Algorithm)
- ACO* (Extended Ant Colony Optimization)
- API
- CACO (Continuous Ant Colony Optimization)
- CGM (Conjugated Gradient Method)
- Brent line search w/o derivatives
- Fletcher-Reeves, Polak-Ribiere, Beale-Sorenson/Hestenes-Stiefel updates
- CMA-ES (Covariance Matrix Adaptation Evolution Strategy)
- two versions of original CMA-ES
- IPOP-CMA-ES (Increasing Population CMA-ES)
- History IPOP-CMA-ES
- DACO (Direct Ant Colony Optimization)
- Deterministic Crowding GA
- Differential Evolution
- two versions
- DIRECT (Dividing Rectangle Optimization)
- Evolutionary Strategy
- Genetic Algorithm
- HGAPSO (Hybrid of the GA and the PSO)
- Levenberg-Marquardt
- Orthogonal Search
- Parallel Hillclimbing
- PBIL (Population Based Incremental Learning)
- Powell
- Brent line search w/o derivatives
- PSO (Particle Swarm Optimization)
- Quasi Newton
- Davidon-Fletcher-Powell, Broyden, Broyden Family, Broyden-Fletcher-Goldfarb-Shanno (BFGS) update
- Random Search
- SADE Genetic Algorithm
- Sequential Niching
- Steepest Descent
- Brent line search w/o derivatives
GUI application is distibuted along with the library. You can use it to quickly compare algorithms and visualize their convergence. The following figure show a visualization of DIviding RECTangle method optimizing two dimensional Rosenbrock's function. Note the regular sampling pattern.
The sampling by means of Particle Swarm Optimization looks quite different.
Quasi Newton will be the method of choice for this problem.
© Vladimír Bičík, Jan Drchal, Martin Hvizdoš, Pavel Kordík, Roman Machytka, Martin Miklánek, Antonín Šulc, FEL ČVUT, 2012