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: about 2 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 7 years ago)
- Default Branch: master
- Last Pushed: 2018-09-17T07:47:44.000Z (over 6 years ago)
- Last Synced: 2025-02-03T06:52:43.649Z (3 months ago)
- Topics: ant-colony-optimization, crossover, evolutionary-algorithms, genetic-programming, hyper-heuristic, mutation, timetabling, tsp-problem
- Language: Swift
- Size: 297 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
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
# An indirect encoding for exam timetabling
Mutating an indirectly-encoded timetable
# Ant Colony Optimization
ACO for 4-City TSP Problem
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
 Global pheromone update
