IDEAS home Printed from https://ideas.repec.org/a/eee/oprepe/v6y2019ics221471601930096x.html

Optimal paths in multi-stage stochastic decision networks

Author

Listed:
  • Roohnavazfar, Mina
  • Manerba, Daniele
  • De Martin, Juan Carlos
  • Tadei, Roberto

Abstract

This paper deals with the search of optimal paths in a multi-stage stochastic decision network as a first application of the deterministic approximation approach proposed by Tadei et al. [48]. In the network, the involved utilities are stage-dependent and contain random oscillations with an unknown probability distribution. The problem is modeled as a sequential choice of nodes in a graph layered into stages, in order to find the optimal path value in a recursive fashion. It is also shown that an optimal path solution can be derived by using a Nested Multinomial Logit model, which represents the choice probability at the different stages. The accuracy and efficiency of the proposed method are experimentally proved on a large set of randomly generated instances. Moreover, insights on the calibration of a critical parameter of the deterministic approximation are also provided.

Suggested Citation

  • Roohnavazfar, Mina & Manerba, Daniele & De Martin, Juan Carlos & Tadei, Roberto, 2019. "Optimal paths in multi-stage stochastic decision networks," Operations Research Perspectives, Elsevier, vol. 6(C).
    • Handle: RePEc:eee:oprepe:v:6:y:2019:i:c:s221471601930096x
    DOI: 10.1016/j.orp.2019.100124
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S221471601930096X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.orp.2019.100124?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Manerba, Daniele & Mansini, Renata & Riera-Ledesma, Jorge, 2017. "The Traveling Purchaser Problem and its variants," European Journal of Operational Research, Elsevier, vol. 259(1), pages 1-18.
    2. Perboli, Guido & Tadei, Roberto & Gobbato, Luca, 2014. "The Multi-Handler Knapsack Problem under Uncertainty," European Journal of Operational Research, Elsevier, vol. 236(3), pages 1000-1007.
    3. Henke, Tino & Speranza, M. Grazia & Wäscher, Gerhard, 2015. "The multi-compartment vehicle routing problem with flexible compartment sizes," European Journal of Operational Research, Elsevier, vol. 246(3), pages 730-743.
    4. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    5. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    6. Manerba, Daniele & Mansini, Renata & Perboli, Guido, 2018. "The Capacitated Supplier Selection problem with Total Quantity Discount policy and Activation Costs under uncertainty," International Journal of Production Economics, Elsevier, vol. 198(C), pages 119-132.
    7. Nickel, Stefan & Saldanha-da-Gama, Francisco & Ziegler, Hans-Peter, 2012. "A multi-stage stochastic supply network design problem with financial decisions and risk management," Omega, Elsevier, vol. 40(5), pages 511-524.
    8. Alejandro Toriello & William B. Haskell & Michael Poremba, 2014. "A Dynamic Traveling Salesman Problem with Stochastic Arc Costs," Operations Research, INFORMS, vol. 62(5), pages 1107-1125, October.
    9. Hartmann, Sönke & Briskorn, Dirk, 2010. "A survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 207(1), pages 1-14, November.
    10. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    11. Lee, Wen-Chiung & Wu, Chin-Chia & Hsu, Peng-Hsiang, 2010. "A single-machine learning effect scheduling problem with release times," Omega, Elsevier, vol. 38(1-2), pages 3-11, February.
    12. Marley, A. A. J., 2002. "Random utility models and their applications: recent developments," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 289-302, July.
    13. Lu Liu & Jian-Jun Wang & Xiao-Yuan Wang, 2016. "Single machine due-window assignment scheduling with resource-dependent processing times to minimise total resource consumption cost," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1186-1195, February.
    14. Baldi, Mauro Maria & Crainic, Teodor Gabriel & Perboli, Guido & Tadei, Roberto, 2012. "The generalized bin packing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1205-1220.
    15. Akamatsu, Takashi, 1996. "Cyclic flows, Markov process and stochastic traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 30(5), pages 369-386, October.
    16. E. Angelelli & R. Mansini & M. Vindigni, 2016. "The Stochastic and Dynamic Traveling Purchaser Problem," Transportation Science, INFORMS, vol. 50(2), pages 642-658, May.
    17. Mosca, Alyssa & Vidyarthi, Navneet & Satir, Ahmet, 2019. "Integrated transportation – inventory models: A review," Operations Research Perspectives, Elsevier, vol. 6(C).
    18. James E. Kelley, 1961. "Critical-Path Planning and Scheduling: Mathematical Basis," Operations Research, INFORMS, vol. 9(3), pages 296-320, June.
    19. Barbara Glensk & Reinhard Madlener, 2013. "Multi-period portfolio optimization of power generation assets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 23(4), pages 20-38.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mina Roohnavazfar & Daniele Manerba & Lohic Fotio Tiotsop & Seyed Hamid Reza Pasandideh & Roberto Tadei, 2021. "Stochastic single machine scheduling problem as a multi-stage dynamic random decision process," Computational Management Science, Springer, vol. 18(3), pages 267-297, July.
    2. Herbon, Avi & David, Israel, 2023. "Optimal manufacturer's cost sharing ratio, shipping policy and production rate – A two-echelon supply chain," Operations Research Perspectives, Elsevier, vol. 10(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mina Roohnavazfar & Daniele Manerba & Lohic Fotio Tiotsop & Seyed Hamid Reza Pasandideh & Roberto Tadei, 2021. "Stochastic single machine scheduling problem as a multi-stage dynamic random decision process," Computational Management Science, Springer, vol. 18(3), pages 267-297, July.
    2. Baldi, Mauro Maria & Manerba, Daniele & Perboli, Guido & Tadei, Roberto, 2019. "A Generalized Bin Packing Problem for parcel delivery in last-mile logistics," European Journal of Operational Research, Elsevier, vol. 274(3), pages 990-999.
    3. Palomo-Martínez, Pamela J. & Salazar-Aguilar, M. Angélica, 2019. "The bi-objective traveling purchaser problem with deliveries," European Journal of Operational Research, Elsevier, vol. 273(2), pages 608-622.
    4. Mathias A. Klapp & Alan L. Erera & Alejandro Toriello, 2018. "The One-Dimensional Dynamic Dispatch Waves Problem," Transportation Science, INFORMS, vol. 52(2), pages 402-415, March.
    5. Mogens Fosgerau & Mads Paulsen & Thomas Kj{ae}r Rasmussen, 2021. "A perturbed utility route choice model," Papers 2103.13784, arXiv.org, revised Sep 2021.
    6. Kitthamkesorn, Songyot & Chen, Anthony, 2014. "Unconstrained weibit stochastic user equilibrium model with extensions," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 1-21.
    7. Gu, Wenjuan & Archetti, Claudia & Cattaruzza, Diego & Ogier, Maxime & Semet, Frédéric & Speranza, M. Grazia, 2024. "Vehicle routing problems with multiple commodities: A survey," European Journal of Operational Research, Elsevier, vol. 317(1), pages 1-15.
    8. Benita, Francisco & López-Ramos, Francisco & Nasini, Stefano, 2019. "A bi-level programming approach for global investment strategies with financial intermediation," European Journal of Operational Research, Elsevier, vol. 274(1), pages 375-390.
    9. Timothy M. Sweda & Irina S. Dolinskaya & Diego Klabjan, 2017. "Adaptive Routing and Recharging Policies for Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1326-1348, November.
    10. Mingyu Xiao & Jianan Zhang & Weibo Lin, 0. "Parameterized algorithms and complexity for the traveling purchaser problem and its variants," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-17.
    11. Roberto Tadei & Guido Perboli & Francesca Perfetti, 2017. "The multi-path Traveling Salesman Problem with stochastic travel costs," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 3-23, March.
    12. Perboli, Guido & Brotcorne, Luce & Bruni, Maria Elena & Rosano, Mariangela, 2021. "A new model for Last-Mile Delivery and Satellite Depots management: The impact of the on-demand economy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    13. Valle, C.A. & Meade, N. & Beasley, J.E., 2014. "Absolute return portfolios," Omega, Elsevier, vol. 45(C), pages 20-41.
    14. Christian Billing & Florian Jaehn & Thomas Wensing, 2018. "A multiperiod auto-carrier transportation problem with probabilistic future demands," Journal of Business Economics, Springer, vol. 88(7), pages 1009-1028, September.
    15. Sophia Saller & Jana Koehler & Andreas Karrenbauer, 2025. "A survey on approximability of traveling salesman problems using the TSP-T3CO definition scheme," Annals of Operations Research, Springer, vol. 351(3), pages 2129-2190, August.
    16. Mohammad Khosroabadi & Jafar Gheidar-Kheljani & Mohammad Hosein Karimi Gavareshki, 2024. "Utilizing Multi-vehicle Traveling Purchaser Problem for Multiple-Supplier Selection and Multi-period Lot-Sizing in a Fuzzy Demand Environment," SN Operations Research Forum, Springer, vol. 5(4), pages 1-28, December.
    17. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    18. Maskooki, Alaleh & Deb, Kalyanmoy & Kallio, Markku, 2022. "A customized genetic algorithm for bi-objective routing in a dynamic network," European Journal of Operational Research, Elsevier, vol. 297(2), pages 615-629.
    19. Evanthia Kazagli & Michel Bierlaire & Matthieu de Lapparent, 2020. "Operational route choice methodologies for practical applications," Transportation, Springer, vol. 47(1), pages 43-74, February.
    20. Pablo A. Miranda-Gonzalez & Javier Maturana-Ross & Carola A. Blazquez & Guillermo Cabrera-Guerrero, 2021. "Exact Formulation and Analysis for the Bi-Objective Insular Traveling Salesman Problem," Mathematics, MDPI, vol. 9(21), pages 1-33, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:oprepe:v:6:y:2019:i:c:s221471601930096x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/operations-research-perspectives .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.