https://github.com/caiocarneloz/nature-inspired

Basic nature-inspired algorithms developed to a master's class lesson
https://github.com/caiocarneloz/nature-inspired

genetic-algorithm machine-learning nature-inspired-algorithms optimization-algorithms

Last synced: about 1 month ago
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Basic nature-inspired algorithms developed to a master's class lesson

• Host: GitHub
• URL: https://github.com/caiocarneloz/nature-inspired
• Owner: caiocarneloz
• Created: 2019-05-12T01:11:03.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-06-12T20:01:27.000Z (over 5 years ago)
• Last Synced: 2023-10-19T21:03:49.209Z (about 1 year ago)
• Topics: genetic-algorithm, machine-learning, nature-inspired-algorithms, optimization-algorithms
• Language: C++
• Size: 9.77 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# nature-inspired

Basic nature-inspired algorithms developed to a master's class lesson

## Fitness Functions

Fitness functions used in the genetic algorithm are defined in **GeneticAlgorithm.cpp**. However the functions used in Hill Climbing and Simmulated Annealing are defined in **utilities.cpp** as "rate". Two of them are math functions to be minimized or maximized. The last one is a Hamming Distance to calculate the difference between pixels of a image.

## Hill Climbing

The Hill Climbing algorithms just get as parameter the number of iterations.

There are three different implementations for this algorithm, as below:

- Hill Climbing

- Iterative Hill Climbing

- Stochastic Hill Climbing

Which can be used by typing:

```

HC(max_it)

IHC(max_it)

SHC(max_it)

```

## Simmulated Annealing

The Simmulated Annealing algorithm receive as parameter just the temperature to be used. You can call the function as below:

```

SA(temperature)

```

The decrease value can be changed in the hardcode.

## Genetic Algorithm