Scilab 5.5.2
- Scilab Help
- Scilab
- Differential calculus, Integration
- Elementary Functions
- Linear Algebra
- Interpolation
- CACSD (Computer Aided Control Systems Design)
- Polynomials
- Signal Processing
- FFTW
- Special Functions
- Randlib
- ARnoldi PACKage (ARPACK binding)
- Statistics
- Sparse Matrix
- UMFPACK Interface (sparse)
- Optimization and Simulation
- Genetic Algorithms
- Simulated Annealing
- XML Management
- HDF5 Management
- Files : Input/Output functions
- Input/Output functions
- Graphics
- Graphics : exporting and printing
- GUI
- Data Structures
- Parameters
- Boolean
- Integers
- Strings
- Sound file handling
- Time and Date
- Output functions
- Xcos
- Spreadsheet
- Console
- History manager
- Matlab binary files I/O
- Matlab to Scilab Conversion Tips
- Compatibility Functions
- Advanced functions
- Development tools
- Demo Tools
- Dynamic/incremental Link
- ATOMS
- Tcl/Tk Interface
- Text editor (Scinotes)
- UI Data
- Online help management
- Parallel
- Modules manager
- Scilab MPI
- Localization
- API Scilab
- call_scilab API (Scilab engine)
- Java Virtual Machine (JVM)
- Java from Scilab
- Java Interface
- Intersci
- Preferences
- Windows tools
Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
However, this page did not exist in the previous stable version.
Genetic Algorithms
- Algorithms
- optim_ga — A flexible genetic algorithm
- optim_moga — multi-objective genetic algorithm
- optim_nsga — A multi-objective Niched Sharing Genetic Algorithm
- optim_nsga2 — A multi-objective Niched Sharing Genetic Algorithm version 2
- Utilities
- coding_ga_binary — A function which performs conversion between binary and continuous representation
- coding_ga_identity — A "no-operation" conversion function
- crossover_ga_binary — A crossover function for binary code
- crossover_ga_default — A crossover function for continuous variable functions
- init_ga_default — A function a initialize a population
- mutation_ga_binary — A function which performs binary mutation
- mutation_ga_default — A continuous variable mutation function
- output_ga_default — A simple output function used for logging purposes
- pareto_filter — A function which extracts non dominated solution from a set
- selection_ga_elitist — An 'elitist' selection function
- selection_ga_random — A function which performs a random selection of individuals
Report an issue | ||
<< Optimization and Simulation | Scilab Help | Simulated Annealing >> |