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Online optimization with gradual look-ahead

Author

Listed:
  • Fabian Dunke

    (Karlsruhe Institute of Technology)

  • Stefan Nickel

    (Karlsruhe Institute of Technology)

Abstract

We extend the setting of online optimization with look-ahead to online optimization with gradual look-ahead. While look-ahead as considered so far refers to a deterministic outlook on future data, gradual look-ahead only allows for an uncertain outlook on future data which becomes more and more precise as an input element’s release time is approached. After a discussion of related concepts, we formally introduce the class of online optimization problems with gradual look-ahead. Since the course of look-ahead information of a single input element is tied to a corresponding uncertainty set trajectory, we examine how different forecasting methods and different algorithmic approaches for dealing with gradual look-ahead can be instantiated and compared to each other with respect to the optimization output. We exemplify the introduced concepts by numerical experiments for the two applications of lot sizing and vehicle routing under gradual look-ahead.

Suggested Citation

  • Fabian Dunke & Stefan Nickel, 2021. "Online optimization with gradual look-ahead," Operational Research, Springer, vol. 21(4), pages 2489-2523, December.
    • Handle: RePEc:spr:operea:v:21:y:2021:i:4:d:10.1007_s12351-019-00506-z
    DOI: 10.1007/s12351-019-00506-z
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    References listed on IDEAS

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    1. Patrick Jaillet & Michael R. Wagner, 2006. "Online Routing Problems: Value of Advanced Information as Improved Competitive Ratios," Transportation Science, INFORMS, vol. 40(2), pages 200-210, May.
    2. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
    3. Li, Jing-Quan & Mirchandani, Pitu B. & Borenstein, Denis, 2009. "Real-time vehicle rerouting problems with time windows," European Journal of Operational Research, Elsevier, vol. 194(3), pages 711-727, May.
    4. Dunke, Fabian & Nickel, Stefan, 2016. "A general modeling approach to online optimization with lookahead," Omega, Elsevier, vol. 63(C), pages 134-153.
    5. Suresh Chand & Suresh Sethi, 2014. "Multi-Period Lot-Sizing with Stationary Demand: Extension to Forecast Horizons," International Series in Operations Research & Management Science, in: Tsan-Ming Choi (ed.), Handbook of EOQ Inventory Problems, edition 127, pages 23-42, Springer.
    6. Josef Kallrath & Thomas I. Maindl, 2006. "Real Optimization with SAP® APO," Springer Books, Springer, number 978-3-540-34624-1, September.
    7. Mitrovic-Minic, Snezana & Krishnamurti, Ramesh & Laporte, Gilbert, 2004. "Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 669-685, September.
    8. Dunke, Fabian & Heckmann, Iris & Nickel, Stefan & Saldanha-da-Gama, Francisco, 2018. "Time traps in supply chains: Is optimal still good enough?," European Journal of Operational Research, Elsevier, vol. 264(3), pages 813-829.
    9. Ghiani, Gianpaolo & Guerriero, Francesca & Laporte, Gilbert & Musmanno, Roberto, 2003. "Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies," European Journal of Operational Research, Elsevier, vol. 151(1), pages 1-11, November.
    10. Curcio, Eduardo & Amorim, Pedro & Zhang, Qi & Almada-Lobo, Bernardo, 2018. "Adaptation and approximate strategies for solving the lot-sizing and scheduling problem under multistage demand uncertainty," International Journal of Production Economics, Elsevier, vol. 202(C), pages 81-96.
    11. C. Bes & S. P. Sethi, 1988. "Concepts of Forecast and Decision Horizons: Applications to Dynamic Stochastic Optimization Problems," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 295-310, May.
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