IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v47y2001i12p1681-1692.html
   My bibliography  Save this article

An Optimization Framework for Product Design

Author

Listed:
  • Leyuan Shi

    (Department of Industrial Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706)

  • Sigurdur Ólafsson

    (Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa 50011)

  • Qun Chen

    (Department of Industrial Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706)

Abstract

An important problem in the product design and development process is to use the part-worths preferences of potential customers to design a new product such that market share is maximized. The authors present a new optimization framework for this problem, the nested partitions (NP) method. This method is globally convergent and may utilize existing heuristic methods to speed its convergence. We incorporate several known heuristics into this framework and demonstrate through numerical experiments that using the NP method results in superior product designs. Our numerical results suggest that the new framework is particularly useful for designing complex products with many attributes.

Suggested Citation

  • Leyuan Shi & Sigurdur Ólafsson & Qun Chen, 2001. "An Optimization Framework for Product Design," Management Science, INFORMS, vol. 47(12), pages 1681-1692, December.
    • Handle: RePEc:inm:ormnsc:v:47:y:2001:i:12:p:1681-1692
    DOI: 10.1287/mnsc.47.12.1681.10243
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.47.12.1681.10243
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.47.12.1681.10243?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
    ---><---

    References listed on IDEAS

    as
    1. P. V. (Sundar) Balakrishnan & Varghese S. Jacob, 1996. "Genetic Algorithms for Product Design," Management Science, INFORMS, vol. 42(8), pages 1105-1117, August.
    2. Kohli, Rajeev & Krishnamurti, Ramesh, 1989. "Optimal product design using conjoint analysis: Computational complexity and algorithms," European Journal of Operational Research, Elsevier, vol. 40(2), pages 186-195, May.
    3. Sunder Kekre & Kannan Srinivasan, 1990. "Broader Product Line: A Necessity to Achieve Success?," Management Science, INFORMS, vol. 36(10), pages 1216-1232, October.
    4. Paul E. Green & Abba M. Krieger, 1985. "Models and Heuristics for Product Line Selection," Marketing Science, INFORMS, vol. 4(1), pages 1-19.
    5. Rajeev Kohli & Ramesh Krishnamurti, 1987. "A Heuristic Approach to Product Design," Management Science, INFORMS, vol. 33(12), pages 1523-1533, December.
    6. Suresh K. Nair & Lakshman S. Thakur & Kuang-Wei Wen, 1995. "Near Optimal Solutions for Product Line Design and Selection: Beam Search Heuristics," Management Science, INFORMS, vol. 41(5), pages 767-785, May.
    7. Green, Paul E. & Krieger, Abba M., 1989. "Recent contributions to optimal product positioning and buyer segmentation," European Journal of Operational Research, Elsevier, vol. 41(2), pages 127-141, July.
    8. Paul E. Green & Abba M. Krieger, 1992. "An Application of a Product Positioning Model to Pharmaceutical Products," Marketing Science, INFORMS, vol. 11(2), pages 117-132.
    9. Rajeev Kohli & R. Sukumar, 1990. "Heuristics for Product-Line Design Using Conjoint Analysis," Management Science, INFORMS, vol. 36(12), pages 1464-1478, December.
    10. Gregory Dobson & Shlomo Kalish, 1993. "Heuristics for Pricing and Positioning a Product-Line Using Conjoint and Cost Data," Management Science, INFORMS, vol. 39(2), pages 160-175, February.
    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. Hao Howard Zhang & Leyuan Shi & Robert Meyer & Daryl Nazareth & Warren D'Souza, 2009. "Solving Beam-Angle Selection and Dose Optimization Simultaneously via High-Throughput Computing," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 427-444, August.
    2. Yoo, Seung Ho, 2014. "Product quality and return policy in a supply chain under risk aversion of a supplier," International Journal of Production Economics, Elsevier, vol. 154(C), pages 146-155.
    3. 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.
    4. Wu, Tao & Shi, Leyuan & Geunes, Joseph & AkartunalI, Kerem, 2011. "An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging," European Journal of Operational Research, Elsevier, vol. 214(2), pages 428-441, October.
    5. Stelios Tsafarakis, 2016. "Redesigning product lines in a period of economic crisis: a hybrid simulated annealing algorithm with crossover," Annals of Operations Research, Springer, vol. 247(2), pages 617-633, December.
    6. Eder Oliveira Abensur, 2007. "Genetic Algorithms for Development of New Financial Products," Brazilian Review of Finance, Brazilian Society of Finance, vol. 5(1), pages 59-77.
    7. Yoo, Seung Ho & Shin, Hojung & Park, Myung-Sub, 2015. "New product development and the effect of supplier involvement," Omega, Elsevier, vol. 51(C), pages 107-120.
    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. James Cochran & David Curry & Rajesh Radhakrishnan & Jon Pinnell, 2014. "Political engineering: optimizing a U.S. Presidential candidate’s platform," Annals of Operations Research, Springer, vol. 215(1), pages 63-87, April.
    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. Wang, Xuping & Ruan, Junhu & Shi, Yan, 2012. "A recovery model for combinational disruptions in logistics delivery: Considering the real-world participators," International Journal of Production Economics, Elsevier, vol. 140(1), pages 508-520.
    12. 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.
    13. Wang, Xinfang (Jocelyn) & Curry, David J., 2012. "A robust approach to the share-of-choice product design problem," Omega, Elsevier, vol. 40(6), pages 818-826.
    14. Jeffrey D. Camm & James J. Cochran & David J. Curry & Sriram Kannan, 2006. "Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem," Management Science, INFORMS, vol. 52(3), pages 435-447, March.

    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. Winfried J. Steiner & Harald Hruschka, 2002. "Produktliniengestaltung mit Genetischen Algorithmen," Schmalenbach Journal of Business Research, Springer, vol. 54(7), pages 575-601, November.
    2. 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.
    3. Albritton, M. David & McMullen, Patrick R., 2007. "Optimal product design using a colony of virtual ants," European Journal of Operational Research, Elsevier, vol. 176(1), pages 498-520, January.
    4. G. E. Fruchter & A. Fligler & R. S. Winer, 2006. "Optimal Product Line Design: Genetic Algorithm Approach to Mitigate Cannibalization," Journal of Optimization Theory and Applications, Springer, vol. 131(2), pages 227-244, November.
    5. 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.
    6. Baier, Daniel & Gaul, Wolfgang, 1998. "Optimal product positioning based on paired comparison data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 365-392, November.
    7. Daria Dzyabura & Srikanth Jagabathula, 2018. "Offline Assortment Optimization in the Presence of an Online Channel," Management Science, INFORMS, vol. 64(6), pages 2767-2786, June.
    8. Alexouda, Georgia & Paparrizos, Konstantinos, 2001. "A genetic algorithm approach to the product line design problem using the seller's return criterion: An extensive comparative computational study," European Journal of Operational Research, Elsevier, vol. 134(1), pages 165-178, October.
    9. V. Krishnan & Rahul Singh & Devanath Tirupati, 1999. "A Model-Based Approach for Planning and Developing a Family of Technology-Based Products," Manufacturing & Service Operations Management, INFORMS, vol. 1(2), pages 132-156.
    10. 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.
    11. Tarasewich, Peter & McMullen, Patrick R., 2001. "A pruning heuristic for use with multisource product design," European Journal of Operational Research, Elsevier, vol. 128(1), pages 58-73, January.
    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. Jeffrey D. Camm & James J. Cochran & David J. Curry & Sriram Kannan, 2006. "Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem," Management Science, INFORMS, vol. 52(3), pages 435-447, March.
    14. 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.
    15. Wilhelm, Wilbert E. & Xu, Kaihong, 2002. "Prescribing product upgrades, prices and production levels over time in a stochastic environment," European Journal of Operational Research, Elsevier, vol. 138(3), pages 601-621, May.
    16. Nair, Suresh K. & Tarasewich, Peter, 2003. "A model and solution method for multi-period sales promotion design," European Journal of Operational Research, Elsevier, vol. 150(3), pages 672-687, November.
    17. 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.
    18. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    19. Sarangi, Subrat & Chakraborty, Abhishek & Triantis, Konstantinos P., 2021. "Multimarket competition effects on product line decisions – A multi-objective decision model in fast moving consumer goods industry," Journal of Business Research, Elsevier, vol. 133(C), pages 388-398.
    20. Stelios Tsafarakis, 2016. "Redesigning product lines in a period of economic crisis: a hybrid simulated annealing algorithm with crossover," Annals of Operations Research, Springer, vol. 247(2), pages 617-633, December.

    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:inm:ormnsc:v:47:y:2001:i:12:p:1681-1692. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.