traveling-salesman-problem
CommunityOptimize routes, minimize travel distance.
Software Engineering#heuristics#logistics#route optimization#operations research#metaheuristics#tsp#combinatorial optimization
Authorkishorkukreja
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill solves the Traveling Salesman Problem (TSP) by finding the shortest possible route that visits each city exactly once and returns to the origin city.
Core Features & Use Cases
- Exact Algorithms: Solves small TSP instances optimally using dynamic programming (Held-Karp).
- MIP Formulation: Solves medium-sized instances using Mixed-Integer Programming (MTZ formulation with PuLP).
- Heuristics: Provides efficient solutions for larger instances using Nearest Neighbor, Cheapest Insertion, 2-Opt, 3-Opt, and Or-Opt.
- Metaheuristics: Employs Simulated Annealing, Genetic Algorithms, and Ant Colony Optimization for complex problems.
- Google OR-Tools: Leverages a powerful solver for practical, large-scale TSP instances.
- Use Case: A logistics company needs to find the most efficient delivery route for its fleet, visiting 50 different customer locations. This Skill can calculate the optimal sequence of stops to minimize fuel consumption and delivery time.
Quick Start
Use the traveling-salesman-problem skill to find the shortest route for 10 cities using the provided distance matrix.
Dependency Matrix
Required Modules
numpypulportools
Components
scriptsreferences
💻 Claude Code Installation
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Please help me install this Skill: Name: traveling-salesman-problem Download link: https://github.com/kishorkukreja/awesome-supply-chain/archive/main.zip#traveling-salesman-problem Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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