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The Constrained Joint Replenishment Problem Using Direct and Indirect Grouping Strategies with Genetic Algorithms

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Abstract

The Joint replenishment problem (JRP) is a model for inventory optimization when ordering multiple products is required. This model allows reducing total inventory costs compared to the practice of performing individual optimization of each product. The saving cost is produced by sharing the fixed ordering costs between several products. The JRP model can be solved using two strategies: the direct grouping strategy (DGS) and the indirect grouping strategy (IGS), which vary in the way the products are grouped. As it can be seen in this chapter, several authors use the JRP model in its simplest version, but it can be easily extended to include restrictions for approximate the model to more realistic applications. Due to the combinatorial nature and the restriction inclusion to the JRP model, it is necessary to use advanced techniques that allow obtaining good solutions in reasonable computing times. This chapter presents the JRP with resource and capacity constraints, which is solved using two genetic algorithms for the evaluation of the Indirect and the Direct Grouping Strategies (IGS and DGS).

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Authors and Affiliations

  1. Escuela de Negocios, Institución Universitaria CEIPA, Calle 77 Sur No. 40-165, Sabaneta, Antioquia, Colombia

    Julian Andres Zapata-Cortes & Víctor Jaime Saldarriaga-Romero

  2. Departamento de Ingeniería de la Organización, Universidad Nacional de Colombia, Carrera 80 No 65-223, Medellín, Antioquia, Colombia

    Martín Darío Arango-Serna

Authors
  1. Julian Andres Zapata-Cortes
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  2. Martín Darío Arango-Serna
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  3. Víctor Jaime Saldarriaga-Romero
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Correspondence to Julian Andres Zapata-Cortes .

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Editors and Affiliations

  1. Universidad Autónoma de Ciudad Juárez, Ciudad Juárez, Chihuahua, Mexico

    Jorge Luis García Alcaraz

  2. Ciudad Universitaria Meléndez, Universidad del Valle, Valle del Cauca, Colombia

    Leonardo Rivera Cadavid

  3. Universidad de Los Andes, Santiago, Chile

    Rosa Guadalupe González-Ramírez

  4. Informações em Rede Consultoria e Treinamento Ltda, Belo Horizonte, Minas Gerais, Brazil

    George Leal Jamil

  5. Universidad del Pacífico, Lima—Jesús María, Peru

    Mario Gustavo Chong Chong

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Zapata-Cortes, J.A., Arango-Serna, M.D., Saldarriaga-Romero, V.J. (2019). The Constrained Joint Replenishment Problem Using Direct and Indirect Grouping Strategies with Genetic Algorithms. In: García Alcaraz, J., Rivera Cadavid, L., González-Ramírez, R., Leal Jamil, G., Chong Chong, M. (eds) Best Practices in Manufacturing Processes. Springer, Cham. https://doi.org/10.1007/978-3-319-99190-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-99190-0_11

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  • Online ISBN: 978-3-319-99190-0

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