A hybrid matheuristic approach for the integrated location routing problem of the pineapple supply chain

Juan Sebastian Arbelaez Torres, Daniel Mauricio Rodriguez Paloma, Gustavo Gatica, David Álvarez-Martínez, John Willmer Escobar

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a matheuristic approach for the location-routing of industrial platforms of the pineapple supply chain problem. We have proposed a three-phase methodology to solve the considered problem. The first phase consists of obtaining the potential supply in terms of suitability and productivity, the potential location of platforms, and the times of the value chain echelons. In the second phase, a mathematical optimization model for the location problem of platforms considering the coverage in terms of timing is proposed. Finally, the final phase proposes a cluster-routing and a granular reactive tabu search approach for the routing phase. The proposed methodology uses official information on production times, speed, and capacity and georeferenced aptitude, spatial, economic, and land yield information for the first time. The proposed approach has been validated through scenarios, particularly pineapple exports for the Colombian country. The obtained results show the efficiency of the proposed approach.

Original languageEnglish
Pages (from-to)483-498
Number of pages16
JournalDecision Science Letters
Volume13
Issue number2
DOIs
Publication statusPublished - 1 Mar 2024

Keywords

  • Cluster-routing algorithm
  • Facility location
  • Granular reactive search
  • Pineapple
  • Vehicle routing problem

ASJC Scopus subject areas

  • General Decision Sciences

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