# A simple genetic algorithm in java

The following java project contains the java source code and java examples used for a simple genetic algorithm. To run, java Simulation.

The following java project contains the java source code and java examples used for card sorting with genetic algorithm. You have 10 cards numbered 1 to 10.
You have to divide them into 2 piles so that:
The sum of the first pile is as close as possible to 36 and the product of all in second pile is as close as poss to 360

The following Matlab project contains the source code and Matlab examples used for framework for differential steering vehicle.
A framework for a differential steering vehicle controlled by a PID system tuned with a genetic algorithm.

The following Matlab project contains the source code and Matlab examples used for differential steering control by single genetic pid.
A framework for a differential steering vehicle controlled by a PID system tuned with a genetic algorithm.

The following Matlab project contains the source code and Matlab examples used for global maximum point for 3d surface using ga.
This program demonstrates the optimization by genetic algorithm to find the global maximum height for thee dimensional multiple peak surface. The GA operates by real coding method with elitism

The following Matlab project contains the source code and Matlab examples used for mdmtspv ga multiple depot multiple traveling salesmen problem solved by genetic algorithm.
Finds a (near) optimal solution to a variation of the M-TSP (that has a variable number of salesmen) by setting up a GA to search for the shortest route (least distance needed or the salesmen to travel to each city exactly once and return to their starting locations).

The following Matlab project contains the source code and Matlab examples used for machine learning balancing a stack of balls.
A genetic algorithm is used to train a neural network controller to balance a stack of balls by applying a lateral force and a torque to the bottom ball.

The following Matlab project contains the source code and Matlab examples used for community detection use gaussian mixture model .
Overlapping community detection use Gaussian Mixture Model.Use k-means algorithm and genetic algorithm.

The following Matlab project contains the source code and Matlab examples used for genetic algorithm code with/without islands and simulated annealing .
Three functions: genetic algorithm (aga), genetic algorithm with islands (aga_islands) and simulated annealing (asa).

Genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

The following Matlab project contains the source code and Matlab examples used for functional optimization of non linear function using genetic algorithm.
Functional Optimization Of Non linear Function(y=sinx) using Genetic Algorithm. Crossover and mutation are used to generated the other chromosomes. This is repeated for generations to get the maximum value of the nonlinear function.

The following Matlab project contains the source code and Matlab examples used for model determination using genetic algorithm forst kalkwarf thodos model.
We use the genetic algorithm (gatool) to determine the four parameters of the implicit Forst-Kalkwarf-Thodos Model.

The following Matlab project contains the source code and Matlab examples used for model determination using genetic algorithm application to vapour pressure vs temperature equations.
We use the genetic algorithm (gatool) to determine the three parameters of the simple Antoine equation and the six parameters of the Modified Antoine Model.

The following Matlab project contains the source code and Matlab examples used for genetic algorithm to optimise schaffer's f6 function.
I'm pretty sure I have this working correctly.

The following Matlab project contains the source code and Matlab examples used for motion planning for a robot arm by using genetic algorithm.
This code proposes genetic algorithm (GA) to optimize the point-to-point trajectory planning for a 3-link (redundant) robot
arm.

The following Matlab project contains the source code and Matlab examples used for simple example of genetic algorithm for optimization problems.
It is used to generate useful solutions to optimization and search problems.

The following Matlab project contains the source code and Matlab examples used for optimization with matlab and the genetic algorithm and direct search toolbox.
M-files accompanying the " Genetic Algorithms & New Optimization Methods in MATLAB " webinar.

The following Matlab project contains the source code and Matlab examples used for 2d bin packing problem with genetic algorithm.
http://simulations.

The following Matlab project contains the source code and Matlab examples used for turboga a simple genetic algorithm with a powerful performance enhancing tweak.
TurboGA is an augmented version of the Matlab script SpeedyGA (also available on File Exchange).

The following Matlab project contains the source code and Matlab examples used for optimal distribution substations placement using genetic algorithm.
This program uses an Excel data file "DATA.

The following Matlab project contains the source code and Matlab examples used for camouflage evolution simulation with genetic algorithm.
http://simulations.

The following Matlab project contains the source code and Matlab examples used for travelling salesman problem with genetic algorithm.
http://simulations.

The following Matlab project contains the source code and Matlab examples used for genetic algorithm for n queen problem.
EACH INDIVIDUAL:- [1*8] where each column value tells the position of queen in that particular column
FINAL SOLUTION:- each row gives one unique solution in the 'solution' matrix
It has very basic but effective functions of selection,crossover and mutation.

The following Matlab project contains the source code and Matlab examples used for speedyga a fast simple genetic algorithm .
SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language.

The following Matlab project contains the source code and Matlab examples used for genetic algorithm performance.
This function can find the maximum of constrained and unconstrained problems with using of genetic algorithm (real coding). Also the performance of GA is plotted vs. the number of generations (for 2D problems).

The following Matlab project contains the source code and Matlab examples used for genetic algorithm.
example of genetic algorithm on required function

The following Matlab project contains the source code and Matlab examples used for genetic algorithm.
Multimodal Function Optimisation

The following Matlab project contains the source code and Matlab examples used for genetic algorithm.
genetic algorithm (or GA) is a search technique used in computing to find true or approximate solutions to optimization and search problems
for function of 2 variable