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Implementation for the NEOM AI challenge, the program computes the best route based upon the user's chosen preferences.

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Genetic Algorithm

Description

This implementation is for the NEOM AI challenge. The Genetic algorithm (GA) is an implementation for an idea named “Lyra” that computes the best route based upon the user's chosen preferences. Thereby, providing the user with optimal results. GA was chosen because of its features, as GA supports multi-objective problems and it offers good optimization. The random mutation used guarantees, to some extent, that wide range of solutions will be provided. Finally, GA is always able to provide an answer, and the answers get better with time.

Libraries used

  • matplotlib.pyplot which is a collection of functions that make matplotlib work. Each pyplot function makes some change to a figure: e.g. creates a plotting area in a figure. It has been used to showcase the graph.
  • NetworkX which is a package for the creation, manipulation, and functions of complex networks that has been used to build the graph.
  • Pandas which is a high-level data manipulation tool developed. It allows to store and manipulate tabular data in rows of observations and columns of variables. It has been used here to read CSV files.

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Implementation for the NEOM AI challenge, the program computes the best route based upon the user's chosen preferences.

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  • Python 100.0%