1. Proceedings
  2. I3M
  3. 2021
  4. MAS
  5. 10.46354/i3m.2021.mas.023

Machine Learning and Genetic Algorithms to Improve Strategic Retail Management

  • a Agostino Bruzzone , 
  • b Kirill Sinelshchikov, 
  • c Marina Massei, 
  • d Wolfhard Schmidt
  • a, cSimulation Team, SIM4Future, via Trento 43, 16145 Genova, Italy
  • b Simulation Team, Genova, Italy
  • d Wolfhard Schmidt
Cite as
Bruzzone A., Sinelshchikov K., Massei M., Schmidt W. (2021). Machine Learning and Genetic Algorithms to Improve Strategic Retail Management. Proceedings of the 20th International Conference on Modeling & Applied Simulation (MAS 2021), pp. 186-189. DOI: https://doi.org/10.46354/i3m.2021.mas.023

Abstract

The paper presents a case study related to a combination of artificial and natural intelligence in order to find the most effective sales strategy in retail. In particular, it proposes a solution which benefits from the combination of machine learning, genetic algorithms and simulation with a man in the loop approach to allow the decision maker to check additional proposals and to impose different constraints. The comparison of different techniques and their evaluation in terms of usability is presented.

References

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