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simulated-annealing-algorithm

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This project applies Simulated Annealing to solve the Traveling Salesman Problem using Peru's departments as nodes. Through iterative refinement, it finds the shortest route visiting each department once. Visual feedback enhances understanding and debugging, resulting in an optimal solution displayed with total distance.

  • Updated May 24, 2024
  • Python
Travel_Route_Planner_ADS_Kim

This "Travel Route Planner" project optimizes travel plan within budget and distance constraints. Using Knapsack & Greedy Method for budget allocation and dynamic programming for TSP, it offers efficient routes. With geocoding & mapping, it tailors plans for satisfying travel experiences.

  • Updated May 9, 2024
  • Python

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