Scilab Online Help
6.0.1 - English

• Scilab Help
• Scilab
• Differential calculus, Integration
• Elementary Functions
• Linear Algebra
• Interpolation
• Control Systems - CACSD
• Polynomials
• Signal Processing
• FFTW
• Special Functions
• Randlib
• ARnoldi PACKage (ARPACK binding)
• Statistics
• Sparse Matrix
• UMFPACK Interface (sparse)
• Optimization and Simulation
• Genetic Algorithms
• Optimization: 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
• Testing & benchmarking
• Demo Tools
• Dynamic/incremental Link
• Windows tools
• ATOMS
• Tcl/Tk Interface
• Text editor (Scinotes)
• UI Data
• Documentation system
• Parallel
• Modules manager
• Localization
• API Scilab
• call_scilab API (Scilab engine)
• Java Virtual Machine (JVM)
• Java from Scilab
• Java Interface
• Preferences
• Scilab code coverage
• Lint tool (SLint)

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 This page might be outdated.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.

Scilab Help >> Genetic Algorithms

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	Optimization: Annealing >>

---