Model for inventory optimization using genetic algorithms

Authors

  • César Hernando Valencia Niño Universidad Santo Tomás
  • Silvia Nathalia Cáceres Quijano Instituto Alberto Luiz Coimbra (COPPE)

DOI:

https://doi.org/10.15332/iteckne.v8i2.2731

Keywords:

Genetic algorithms, Bullwhip effect, Supply chain optimization, BMN coefficients

Abstract

This paper presents the design of a genetic algorithm (GA) that optimizes inventory management in supply chains. They were considered warehousing, distribution, and manufacturing product costs, plus the cost of individual items to be ordered. The string used in the simulation contains 5 levels, being: customer, retail, warehouse, distributor and factory. The amounts of each pair were considered to be evaluated by the GA in the best chromosome. Additionally the BMN coefficients model was used to generate the evaluation function of chromosomes selected by the GA and satisfies the constraints considered in the model.

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Author Biographies

César Hernando Valencia Niño, Universidad Santo Tomás

D.Sc.(c) da Engenharia Elétrica Pontifícia Universidade Católica do Rio de Janeiro. Investigador Grupo GRAM Universidad Santo Tomás USTA Bucaramanga, Colombia

Silvia Nathalia Cáceres Quijano, Instituto Alberto Luiz Coimbra (COPPE)

M.Sc.(c) da Engenharia de Produção Universidade Federal do Rio de Janeiro. Pesquisadora Programa de Engenharia de Produção Instituto Alberto Luiz Coimbra - COPPE Rio de Janeiro, Brasil

References

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Published

2011-12-12

How to Cite

Valencia Niño, C. H., & Cáceres Quijano, S. N. (2011). Model for inventory optimization using genetic algorithms. ITECKNE, 8(2), 156–162. https://doi.org/10.15332/iteckne.v8i2.2731

Issue

Vol. 8 No. 2 (2011)

Section

Research and Innovation Articles

License

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