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Dynamic search models with multiple items

Author

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  • Rebecca Dizon-Ross

    (University of Chicago Booth School of Business)

  • Sheldon M. Ross

    (University of Southern California)

Abstract

We generalize the classic dynamic single-item search model to a setting with multiple items and vector offers for subsets of items. We first show a computationally feasible way to solve the dynamic optimization problem, and then prove structural results. Although assignment is not generally monotonically increasing in offer value, we show that, in a special case “additive” model, monotonicity holds if costs are submodular. We examine how the thresholds for assignment change with the remaining items, and whether there are gains to grouping searches. Finally, we consider a stopping rule version of the problem with no subsets for sale, showing the optimal policy is myopic.

Suggested Citation

  • Rebecca Dizon-Ross & Sheldon M. Ross, 2020. "Dynamic search models with multiple items," Annals of Operations Research, Springer, vol. 288(1), pages 223-245, May.
    • Handle: RePEc:spr:annopr:v:288:y:2020:i:1:d:10.1007_s10479-019-03472-z
    DOI: 10.1007/s10479-019-03472-z
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    References listed on IDEAS

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    Cited by:

    1. Sheldon M. Ross & Gideon Weiss & Zhengyu Zhang, 2021. "Technical Note—A Stochastic Assignment Problem with Unknown Eligibility Probabilities," Operations Research, INFORMS, vol. 69(1), pages 266-272, January.

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    More about this item

    Keywords

    Dynamic programming; Job search; Multiple applicants; Optimal stopping; Stochastic assignment problem;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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