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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
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    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.

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