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Generalized disjunctive programming models for the truck loading problem: A case study from the non-alcoholic beverages industry

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  • Novas, Juan M.
  • Ramello, Juan Ignacio
  • Rodríguez, María Analía

Abstract

A real-world truck loading problem is considered for the major non-alcoholic beverage bottler in Argentina. The previous manual procedure to define the truck loading plan is improved by automatizing the process through a set of optimization models applying Generalized Disjunctive Programming. Most of the operational practices and restrictions are taken into account. Given that there is flexibility to load products in the trucks, a better use of their capacities is obtained, and the balance of forces addressed avoids expensive penalties fees. By a set of examples, different metrics are tested, and good quality results are obtained for an every-day practice.

Suggested Citation

  • Novas, Juan M. & Ramello, Juan Ignacio & Rodríguez, María Analía, 2020. "Generalized disjunctive programming models for the truck loading problem: A case study from the non-alcoholic beverages industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    • Handle: RePEc:eee:transe:v:140:y:2020:i:c:s1366554520306220
    DOI: 10.1016/j.tre.2020.101971
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    Cited by:

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    2. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).

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