https://github.com/egzonarifi/nature-inspired-algorithms

https://github.com/egzonarifi/nature-inspired-algorithms

ant-colony-optimization crossover evolutionary-algorithms genetic-programming hyper-heuristic mutation timetabling tsp-problem

Last synced: 10 months ago
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• Host: GitHub
• URL: https://github.com/egzonarifi/nature-inspired-algorithms
• Owner: EgzonArifi
• Created: 2017-11-05T09:31:29.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2018-09-17T07:47:44.000Z (over 7 years ago)
• Last Synced: 2025-03-28T21:13:31.065Z (about 1 year ago)
• Topics: ant-colony-optimization, crossover, evolutionary-algorithms, genetic-programming, hyper-heuristic, mutation, timetabling, tsp-problem
• Language: Swift
• Size: 297 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Nature Inspired Algorithms

  macOS Application used to implement different tasks in winter semester

 

 # Hyper-heuristics (HH): a specific type of indirect encoding

  Bin packing problem using FFA, FFD, BF1

 ![Alt text](binpacking.png?raw=true "Title")

# An indirect encoding for exam timetabling

  Mutating an indirectly-encoded timetable

 ![Alt text](timetabling.png?raw=true "Title")

# Ant Colony Optimization

  ACO for 4-City TSP Problem

![Alt text](aco.png?raw=true "Title")

Ants are agents that:

• Move along between nodes in a graph.

• They choose where to go based on pheromone strength (and

maybe other information)

• An ant’s path represents a specific candidate solution.

• When an ant has finished a solution, pheromone is laid on

its path, according to quality of solution.

• This pheromone trail affects behaviour of other ants by `stigmergy`

 Transition Rule

![Alt text](transitionRule.png?raw=true "Title")

 Global pheromone update

![Alt text](globalUpdate.png?raw=true "Title")