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An improved heuristic approach for the interval immune transportation problem

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  • Carrabs, Francesco
  • Cerulli, Raffaele
  • D’Ambrosio, Ciriaco
  • Della Croce, Federico
  • Gentili, Monica

Abstract

We study the problem of determining the bounds of the optimal cost of a transportation problem when the capacity of the suppliers and the demand of the customers vary over an interval. We consider transportation costs such that the transportation paradox does not arise. We design a new heuristic approach based on some polyhedral properties of the problem and provide a novel integer linear programming mathematical formulation to solve it exactly. Our computational results, carried out on benchmark instances from the literature and on some new instances, show that our heuristic algorithm greatly outperforms the best solution approaches currently used.

Suggested Citation

  • Carrabs, Francesco & Cerulli, Raffaele & D’Ambrosio, Ciriaco & Della Croce, Federico & Gentili, Monica, 2021. "An improved heuristic approach for the interval immune transportation problem," Omega, Elsevier, vol. 104(C).
  • Handle: RePEc:eee:jomega:v:104:y:2021:i:c:s0305048321001018
    DOI: 10.1016/j.omega.2021.102492
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    References listed on IDEAS

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    1. Juman, Z.A.M.S. & Hoque, M.A., 2014. "A heuristic solution technique to attain the minimal total cost bounds of transporting a homogeneous product with varying demands and supplies," European Journal of Operational Research, Elsevier, vol. 239(1), pages 146-156.
    2. D’Ambrosio, C. & Gentili, M. & Cerulli, R., 2020. "The optimal value range problem for the Interval (immune) Transportation Problem," Omega, Elsevier, vol. 95(C).
    3. Elif Garajová & Milan Hladík & Miroslav Rada, 2019. "Interval linear programming under transformations: optimal solutions and optimal value range," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 601-614, September.
    4. J W Chinneck & K Ramadan, 2000. "Linear programming with interval coefficients," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(2), pages 209-220, February.
    5. Liu, Shiang-Tai, 2003. "The total cost bounds of the transportation problem with varying demand and supply," Omega, Elsevier, vol. 31(4), pages 247-251, August.
    6. Wlodzimierz Szwarc, 1971. "The transportation paradox," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 18(2), pages 185-202, June.
    7. Xie, Fanrong & Butt, Muhammad Munir & Li, Zuoan & Zhu, Linzhi, 2017. "An upper bound on the minimal total cost of the transportation problem with varying demands and supplies," Omega, Elsevier, vol. 68(C), pages 105-118.
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    Cited by:

    1. Elif Garajová & Miroslav Rada, 2023. "Interval transportation problem: feasibility, optimality and the worst optimal value," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(3), pages 769-790, September.

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