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Optimizing Product Line Designs: Efficient Methods and Comparisons

Author

Listed:
  • Alexandre Belloni

    (The Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Robert Freund

    (MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

  • Matthew Selove

    (MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

  • Duncan Simester

    (MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

Abstract

We take advantage of recent advances in optimization methods and computer hardware to identify globally optimal solutions of product line design problems that are too large for complete enumeration. We then use this guarantee of global optimality to benchmark the performance of more practical heuristic methods. We use two sources of data: (1) a conjoint study previously conducted for a real product line design problem, and (2) simulated problems of various sizes. For both data sources, several of the heuristic methods consistently find optimal or near-optimal solutions, including simulated annealing, divide-and-conquer, product-swapping, and genetic algorithms.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:9:p:1544-1552
    DOI: 10.1287/mnsc.1080.0864
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    References listed on IDEAS

    as
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