https://github.com/vidiptvashist/tsp-ant-colony-optimization

https://github.com/vidiptvashist/tsp-ant-colony-optimization

Last synced: 3 days ago
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• Host: GitHub
• URL: https://github.com/vidiptvashist/tsp-ant-colony-optimization
• Owner: vidiptvashist
• Created: 2022-07-21T19:11:12.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-21T19:13:57.000Z (over 2 years ago)
• Last Synced: 2024-11-13T23:30:36.375Z (2 months ago)
• Language: Jupyter Notebook
• Size: 684 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# TSP-Ant-Colony-Optimization

The algorithmic world is beautiful with multifarious strategies and

tools being developed round the clock to render to the need for highperformance computing. Different optimization techniques have thus

evolved based on such evolutionary algorithms and thereby opened

up the domain of metaheuristics. Metaheuristic has been derived from

two Greek words, namely, Meta meaning one level above and heuriskein

meaning to find. Algorithms such as the Particle Swarm Optimization

(PSO) and Ant Colony Optimization (ACO) are examples of swarm

intelligence and metaheuristics. The goal of swarm intelligence is to

design intelligent multi-agent systems by taking inspiration from the

collective behaviour of social insects such as ants, termites, bees, wasps,

and other animal societies such as flocks of birds or schools of fish