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Genetic Algorithm to solve a TSP problem involving delivering burritos by drone, with time constraints.

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TSP-Drone-delivering-burritos

Genetic Algorithm to solve a TSP problem involving delivering burritos by drone, with time constraints.

Problem:

  • Deliver 100 burritos while trying to minimise customer dis-satisfaction.
  • We are given the time[] array which contains the length of time each customer has been waiting for their burrito.
  • The goal is to minimize the sum of this array while delivering the burritos to the specified locations, given as longitudes and latitudes.
  • The Drone moves at a constant speed.
  • To calculate the distance between points on the path we can use the haversine distance formula for calculating distances along great circles.

Solution:

  • Generate random paths
  • calculate the customer dis-satifaction for each path and track the fitness of a path.
  • implement genetic algorithm which uses crossover & mutation to combine paths without repetition of locations.
  • new populations will be bred from the old population with the fitness playing a role in the probability of a path being chosen.
  • New populations should have improved fitness.
  • Locations are labelled 1-100

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Genetic Algorithm to solve a TSP problem involving delivering burritos by drone, with time constraints.

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