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A Column Generation Approach for Solving a Green Bi-objective Inventory Routing Problem

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Advances in Artificial Intelligence - IBERAMIA 2016 (IBERAMIA 2016)

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Abstract

The aim of this paper is present a multi-objective algorithm embedded with column generation to solve a green bi-objective inventory routing problem. In contrast with the classic Inventory Routing Problem where the main objective is to minimize the total cost overall supply chain network, in the green logistics besides this objective a minimization of the \( CO_{2} \) emisions is included. For solving the bi-objective problem, we proposed the use of NISE (Noninferior Set Estimation) algorithm combined with column generation for reduce the amount of variables in the problem.

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Acknowledgments

We thank Fair Isaac Corporation (FICO) for providing us with Xpress-MP licenses under the Academic Partner Program subscribed with Universidad Distrital Francisco Jose de Caldas (Colombia). Last, but not least, the authors would like to thank the comments of the anonymous referees that significantly improved our paper.

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Authors and Affiliations

  1. Universidad del Rosario, Bogotá, Colombia

    Carlos Franco

  2. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Eduyn Ramiro López-Santana & Germán Méndez-Giraldo

Authors
  1. Carlos Franco
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  2. Eduyn Ramiro López-Santana
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  3. Germán Méndez-Giraldo
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Corresponding author

Correspondence to Carlos Franco .

Editor information

Editors and Affiliations

  1. INAOE , Tonantzintla, Mexico

    Manuel Montes y Gómez

  2. Astrofisica Optica y Electronica, INAOE , Puebla, Mexico

    Hugo Jair Escalante

  3. Universidad Nacional de Costa Rica , Heredia, Costa Rica

    Alberto Segura

  4. Universidad Nacional de Costa Rica , Heredia, Costa Rica

    Juan de Dios Murillo

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Franco, C., López-Santana, E.R., Méndez-Giraldo, G. (2016). A Column Generation Approach for Solving a Green Bi-objective Inventory Routing Problem. In: Montes y Gómez, M., Escalante, H., Segura, A., Murillo, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2016. IBERAMIA 2016. Lecture Notes in Computer Science(), vol 10022. Springer, Cham. https://doi.org/10.1007/978-3-319-47955-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-47955-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47954-5

  • Online ISBN: 978-3-319-47955-2

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