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Fixed Charge Transportation Problems: a new heuristic approach based on Lagrangean relaxation and the solving of core problems

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  • Jesús Sáez Aguado

Abstract

In this paper the Fixed Charge Transportation Problem is considered. A new heuristic approach is proposed, based on the intensive use of Lagrangean relaxation techniques. The more novel aspects of this approach are new Lagrangean relaxation and decomposition methods, the consideration of several core problems, defined from the previously computed Lagrangean reduced costs, the heuristic selection of the most promising core problem and the final resort to enumeration by applying a branch and cut algorithm to the selected core problem. For problems with a small ratio of the average fixed cost to the average variable cost (lower than or equal to 25), the proposed method can obtain similar or better solutions than the state-of-art algorithms, such as the tabu search procedure and the parametric ghost image processes. For larger ratios (between 50 and 180), the quality of the obtained solutions could be considered to be halfway between both methods. Copyright Springer Science+Business Media, LLC 2009

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  • Jesús Sáez Aguado, 2009. "Fixed Charge Transportation Problems: a new heuristic approach based on Lagrangean relaxation and the solving of core problems," Annals of Operations Research, Springer, vol. 172(1), pages 45-69, November.
  • Handle: RePEc:spr:annopr:v:172:y:2009:i:1:p:45-69:10.1007/s10479-008-0483-2
    DOI: 10.1007/s10479-008-0483-2
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    2. Tong, Lu & Zhou, Xuesong & Miller, Harvey J., 2015. "Transportation network design for maximizing space–time accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 555-576.
    3. Adlakha, Veena & Kowalski, Krzysztof & Wang, Simi & Lev, Benjamin & Shen, Wenjing, 2014. "On approximation of the fixed charge transportation problem," Omega, Elsevier, vol. 43(C), pages 64-70.
    4. Yixin Zhao & Torbjörn Larsson & Elina Rönnberg & Panos M. Pardalos, 2018. "The fixed charge transportation problem: a strong formulation based on Lagrangian decomposition and column generation," Journal of Global Optimization, Springer, vol. 72(3), pages 517-538, November.
    5. A. N. Balaji & J. Mukund Nilakantan & Izabela Nielsen & N. Jawahar & S. G. Ponnambalam, 2019. "Solving fixed charge transportation problem with truck load constraint using metaheuristics," Annals of Operations Research, Springer, vol. 273(1), pages 207-236, February.
    6. Kowalski, Krzysztof & Lev, Benjamin & Shen, Wenjing & Tu, Yan, 2014. "A fast and simple branching algorithm for solving small scale fixed-charge transportation problem," Operations Research Perspectives, Elsevier, vol. 1(1), pages 1-5.
    7. Shen, Chan & Sun, Yao & Bai, Zijian & Cui, Hongjun, 2021. "Real-time customized bus routes design with optimal passenger and vehicle matching based on column generation algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    8. Dimitri J. Papageorgiou & Alejandro Toriello & George L. Nemhauser & Martin W. P. Savelsbergh, 2012. "Fixed-Charge Transportation with Product Blending," Transportation Science, INFORMS, vol. 46(2), pages 281-295, May.
    9. V. Adlakha & K. Kowalski, 2015. "Fractional Polynomial Bounds for the Fixed Charge Problem," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 1026-1038, March.

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