Traveling Salesman Problem using linear programming math model, Reinforcement Learning and Simulated Annealing
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Updated
Jun 5, 2024 - Jupyter Notebook
Traveling Salesman Problem using linear programming math model, Reinforcement Learning and Simulated Annealing
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.
⚡Solve the Eight Queens Puzzle with Simulated Annealing for optimal queen placement on a chessboard
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.
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TypeScript implementation of the Simulated Annealing algorithm, offering flexibility to handle various data types and supporting both maximization and minimization objectives.
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Travel Route Planner with Simulated Annealing Algorithm
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We have solved famous Travelling Salesman Problem using an AI algorithm Simulated Annealing
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Python application to create a choreography for the NAO robot so that is fully automatically using AI techniques and suitable for the song that is selected randomly.
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