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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

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# 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")