IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v294y2021i2p492-506.html
   My bibliography  Save this article

The rank pricing problem with ties

Author

Listed:
  • Domínguez, Concepción
  • Labbé, Martine
  • Marín, Alfredo

Abstract

In the Rank Pricing Problem (RPP), a firm intends to maximize its profit through the pricing of a set of products to sell. Customers are interested in purchasing at most one product among a subset of products. To do so, they are endowed with a ranked list of preferences and a budget. Their choice rule consists in purchasing the highest-ranked product in their list and whose price is below their budget. In this paper, we consider an extension of RPP, the Rank Pricing Problem with Ties (RPPT), in which we allow for indifference between products in the list of preferences of the customers. Considering the bilevel structure of the problem, this generalization differs from the RPP in that it can lead to multiple optimal solutions for the second level problems associated to the customers. In such cases, we look for pessimistic optimal solutions of the bilevel problem : the customer selects the cheapest product. We present a new three-indexed integer formulation for RPPT and introduce two resolution approaches. In the first one, we project out the customer decision variables, obtaining a reduced formulation that we then strengthen with valid inequalities from the former formulation. Alternatively, we follow a Benders decomposition approach leveraging the separability of the problem into a master problem and several subproblems. The separation problems to include the valid inequalities to the master problem dynamically are shown to reduce to min-cost flow problems. We finally carry out extensive computational experiments to assess the performance of the resolution approaches.

Suggested Citation

  • Domínguez, Concepción & Labbé, Martine & Marín, Alfredo, 2021. "The rank pricing problem with ties," European Journal of Operational Research, Elsevier, vol. 294(2), pages 492-506.
  • Handle: RePEc:eee:ejores:v:294:y:2021:i:2:p:492-506
    DOI: 10.1016/j.ejor.2021.02.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721001107
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.02.017?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Augustine Kwanashie & David F. Manlove, 2014. "An Integer Programming Approach to the Hospitals/Residents Problem with Ties," Operations Research Proceedings, in: Dennis Huisman & Ilse Louwerse & Albert P.M. Wagelmans (ed.), Operations Research Proceedings 2013, edition 127, pages 263-269, Springer.
    2. Cornelia Schön, 2010. "On the Optimal Product Line Selection Problem with Price Discrimination," Management Science, INFORMS, vol. 56(5), pages 896-902, May.
    3. Gregory Dobson & Shlomo Kalish, 1988. "Positioning and Pricing a Product Line," Marketing Science, INFORMS, vol. 7(2), pages 107-125.
    4. Kyle D. Chen & Warren H. Hausman, 2000. "Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis," Management Science, INFORMS, vol. 46(2), pages 327-332, February.
    5. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    6. Paat Rusmevichientong & Benjamin Van Roy & Peter W. Glynn, 2006. "A Nonparametric Approach to Multiproduct Pricing," Operations Research, INFORMS, vol. 54(1), pages 82-98, February.
    7. Paul E. Green & Abba M. Krieger, 1985. "Models and Heuristics for Product Line Selection," Marketing Science, INFORMS, vol. 4(1), pages 1-19.
    8. Espejo, Inmaculada & Marín, Alfredo & Rodríguez-Chía, Antonio M., 2012. "Closest assignment constraints in discrete location problems," European Journal of Operational Research, Elsevier, vol. 219(1), pages 49-58.
    9. Richard D. McBride & Fred S. Zufryden, 1988. "An Integer Programming Approach to the Optimal Product Line Selection Problem," Marketing Science, INFORMS, vol. 7(2), pages 126-140.
    10. Kraus, Ursula G. & Yano, Candace Arai, 2003. "Product line selection and pricing under a share-of-surplus choice model," European Journal of Operational Research, Elsevier, vol. 150(3), pages 653-671, November.
    11. Alexandre Belloni & Robert Freund & Matthew Selove & Duncan Simester, 2008. "Optimizing Product Line Designs: Efficient Methods and Comparisons," Management Science, INFORMS, vol. 54(9), pages 1544-1552, September.
    12. Delorme, Maxence & García, Sergio & Gondzio, Jacek & Kalcsics, Jörg & Manlove, David & Pettersson, William, 2019. "Mathematical models for stable matching problems with ties and incomplete lists," European Journal of Operational Research, Elsevier, vol. 277(2), pages 426-441.
    13. Schön, Cornelia, 2010. "On the product line selection problem under attraction choice models of consumer behavior," European Journal of Operational Research, Elsevier, vol. 206(1), pages 260-264, October.
    14. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    15. Joe Naoum-Sawaya & Samir Elhedhli, 2013. "An interior-point Benders based branch-and-cut algorithm for mixed integer programs," Annals of Operations Research, Springer, vol. 210(1), pages 33-55, November.
    16. Hanjoul, Pierre & Peeters, Dominique, 1987. "A facility location problem with clients' preference orderings," Regional Science and Urban Economics, Elsevier, vol. 17(3), pages 451-473, August.
    Full references (including those not matched with items on IDEAS)

    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. Bechler, Georg & Steinhardt, Claudius & Mackert, Jochen & Klein, Robert, 2021. "Product line optimization in the presence of preferences for compromise alternatives," European Journal of Operational Research, Elsevier, vol. 288(3), pages 902-917.
    2. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
    3. Andrade, Xavier & Guimarães, Luís & Figueira, Gonçalo, 2021. "Product line selection of fast-moving consumer goods," Omega, Elsevier, vol. 102(C).
    4. Hongmin Li & Scott Webster & Gwangjae Yu, 2020. "Product Design Under Multinomial Logit Choices: Optimization of Quality and Prices in an Evolving Product Line," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1011-1025, September.
    5. Schön, Cornelia, 2010. "On the product line selection problem under attraction choice models of consumer behavior," European Journal of Operational Research, Elsevier, vol. 206(1), pages 260-264, October.
    6. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    7. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
    8. Tan Wang & Genaro Gutierrez, 2022. "Robust Product Line Design by Protecting the Downside While Minding the Upside," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 194-217, January.
    9. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    10. Maoqi Liu & Li Zheng & Changchun Liu & Zhi‐Hai Zhang, 2023. "From share of choice to buyers' welfare maximization: Bridging the gap through distributionally robust optimization," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1205-1222, April.
    11. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    12. Xinfang (Jocelyn) Wang & Jeffrey D. Camm & David J. Curry, 2009. "A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem," Management Science, INFORMS, vol. 55(10), pages 1718-1728, October.
    13. Burkart, Wolfgang R. & Klein, Robert & Mayer, Stefan, 2012. "Product line pricing for services with capacity constraints and dynamic substitution," European Journal of Operational Research, Elsevier, vol. 219(2), pages 347-359.
    14. Steven M. Shugan & Jihwan Moon & JQiaoni Shi & Nanda S. Kumar, 2017. "Product Line Bundling: Why Airlines Bundle High-End While Hotels Bundle Low-End," Marketing Science, INFORMS, vol. 36(1), pages 124-139, January.
    15. Mayer, Stefan & Steinhardt, Claudius, 2016. "Optimal product line pricing in the presence of budget-constrained consumers," European Journal of Operational Research, Elsevier, vol. 248(1), pages 219-233.
    16. Dorothee Honhon & Sreelata Jonnalagedda & Xiajun Amy Pan, 2012. "Optimal Algorithms for Assortment Selection Under Ranking-Based Consumer Choice Models," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 279-289, April.
    17. Kraus, Ursula G. & Yano, Candace Arai, 2003. "Product line selection and pricing under a share-of-surplus choice model," European Journal of Operational Research, Elsevier, vol. 150(3), pages 653-671, November.
    18. Day, Jamison M. & Venkataramanan, M.A., 2006. "Profitability in product line pricing and composition with manufacturing commonalities," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1782-1797, December.
    19. Juan José Miranda Bront & Isabel Méndez-Díaz & Gustavo Vulcano, 2009. "A Column Generation Algorithm for Choice-Based Network Revenue Management," Operations Research, INFORMS, vol. 57(3), pages 769-784, June.
    20. Tallys H. Yunes & Dominic Napolitano & Alan Scheller-Wolf & Sridhar Tayur, 2007. "Building Efficient Product Portfolios at John Deere and Company," Operations Research, INFORMS, vol. 55(4), pages 615-629, August.

    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:ejores:v:294:y:2021:i:2:p:492-506. 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.elsevier.com/locate/eor .

    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.