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A genetic column generation algorithm for sustainable spare part delivery: application to the Sydney DropPoint network

Author

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  • Michelle Dunbar

    (University of Sydney)

  • Simon Belieres

    (l’Institut National des Sciences Appliquées de Toulouse (INSA))

  • Nagesh Shukla

    (University of Technology Sydney)

  • Mehrdad Amirghasemi

    (University of Wollongong)

  • Pascal Perez

    (University of Wollongong)

  • Nishikant Mishra

    (University of Hull)

Abstract

Modern-day logistics companies require increasingly shorter lead-times in order to cater for the increasing popularity of on-demand services. There is consequently an urgent need for fast scheduling algorithms to provide high quality, real-time implementable solutions. In this work we model a spare part delivery problem for an on-demand logistics company, as a variant of vehicle routing problem. For large delivery networks, the optimisation solution technique of column generation has been employed successfully in a variety of vehicle routing settings and is often used in combination with exact methods for solving problems with a large number of variables. Challenges may arise when the pricing subproblem is difficult to solve in a realistic period due to complex constraints or a large number of variables. The problem may become intractable when the network structure varies daily or is known with less certainty over longer period. In such instances, a high quality heuristic solution may be more preferable than an exact solution with excessive run time. We propose an improved version of column generation approach integrating an efficient genetic algorithm to obtain fast and high-quality solutions for a sustainable spare parts delivery problem. More specifically, we propose to retain the traditional column generation iterative framework, with master problem solved exactly, but with pricing subproblem solved using a metaheuristic. Computational results on a real dataset indicate that this approach yields improved solutions compared to the current best-case business-as-usual costs. It also substantially decreases the computational time; allowing for high-quality, tractable solutions to be obtained in few minutes. We propose to strike a balance between the practical and efficient solution aspects of metaheuristic algorithms, and the exact decomposition and iterative aspect of the column generation solution technique.

Suggested Citation

  • Michelle Dunbar & Simon Belieres & Nagesh Shukla & Mehrdad Amirghasemi & Pascal Perez & Nishikant Mishra, 2020. "A genetic column generation algorithm for sustainable spare part delivery: application to the Sydney DropPoint network," Annals of Operations Research, Springer, vol. 290(1), pages 923-941, July.
    • Handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-2911-2
    DOI: 10.1007/s10479-018-2911-2
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    References listed on IDEAS

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    1. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    2. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    3. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    4. Shukla, Nagesh & Choudhary, A.K. & Prakash, P.K.S. & Fernandes, K.J. & Tiwari, M.K., 2013. "Algorithm portfolios for logistics optimization considering stochastic demands and mobility allowance," International Journal of Production Economics, Elsevier, vol. 141(1), pages 146-166.
    5. Nagesh Shukla & Senevi Kiridena, 2016. "A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6984-6996, December.
    6. Jean-Yves Potvin & Samy Bengio, 1996. "The Vehicle Routing Problem with Time Windows Part II: Genetic Search," INFORMS Journal on Computing, INFORMS, vol. 8(2), pages 165-172, May.
    7. D. Espinoza & R. Garcia & M. Goycoolea & G. L. Nemhauser & M. W. P. Savelsbergh, 2008. "Per-Seat, On-Demand Air Transportation Part I: Problem Description and an Integer Multicommodity Flow Model," Transportation Science, INFORMS, vol. 42(3), pages 263-278, August.
    8. Roberto Baldacci & Enrico Bartolini & Aristide Mingozzi, 2011. "An Exact Algorithm for the Pickup and Delivery Problem with Time Windows," Operations Research, INFORMS, vol. 59(2), pages 414-426, April.
    9. Charu C. Aggarwal & James B. Orlin & Ray P. Tai, 1997. "Optimized Crossover for the Independent Set Problem," Operations Research, INFORMS, vol. 45(2), pages 226-234, April.
    10. Jean-Yves Potvin & Tanguy Kervahut & Bruno-Laurent Garcia & Jean-Marc Rousseau, 1996. "The Vehicle Routing Problem with Time Windows Part I: Tabu Search," INFORMS Journal on Computing, INFORMS, vol. 8(2), pages 158-164, May.
    11. Jean-François Cordeau & Gilbert Laporte, 2007. "The dial-a-ride problem: models and algorithms," Annals of Operations Research, Springer, vol. 153(1), pages 29-46, September.
    12. Paolo Toth & Daniele Vigo, 1997. "Heuristic Algorithms for the Handicapped Persons Transportation Problem," Transportation Science, INFORMS, vol. 31(1), pages 60-71, February.
    13. Paquette, Julie & Cordeau, Jean-François & Laporte, Gilbert & Pascoal, Marta M.B., 2013. "Combining multicriteria analysis and tabu search for dial-a-ride problems," Transportation Research Part B: Methodological, Elsevier, vol. 52(C), pages 1-16.
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