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Hourly Staff Planning With Genetic Algorithms

-- Project Status: [Completed]

Project Intro/Objective

Staff planning is a topic of optimization research that comes back in many companies. As soon as a company has many employees, it becomes hard to find planning that suits the business needs while respecting certain constraints. The purpose of this project is to implement genetic algorithms to find an optimal hourly staff planning solution.

Methods Used

  • Genetic Algorithms

Technologies

  • Python
  • Jupyter
  • Numpy
  • Pandas

Project Description

A genetic algorithm is a search heuristic that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.They operate on string structures, like biological structures, which are evolving in time. In this project, I implement genetic algorithms to find an optimal hourly staff planning solution.

Featured Notebooks/Analysis/Deliverables

Contributing Members

Luke Monington

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