Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/75928
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Sun, H | en_US |
dc.creator | Su, CL | en_US |
dc.creator | Chen, X | en_US |
dc.date.accessioned | 2018-05-10T02:54:58Z | - |
dc.date.available | 2018-05-10T02:54:58Z | - |
dc.identifier.issn | 0025-5610 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/75928 | - |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.rights | © Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society 2017 | en_US |
dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10107-017-1119-6 | en_US |
dc.subject | Stochastic linear complementarity problem | en_US |
dc.subject | Epi-convergence | en_US |
dc.subject | Lower/upper semicontinuous | en_US |
dc.subject | Sample average approximation | en_US |
dc.subject | Regularized monotone linear complementarity problem | en_US |
dc.subject | Multiproduct pricing | en_US |
dc.title | SAA-regularized methods for multiproduct price optimization under the pure characteristics demand model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 361 | en_US |
dc.identifier.epage | 389 | en_US |
dc.identifier.volume | 165 | en_US |
dc.identifier.issue | 1 | en_US |
dc.identifier.doi | 10.1007/s10107-017-1119-6 | en_US |
dcterms.abstract | Utility-based choice models are often used to determine a consumer's purchase decision among a list of available products; to provide an estimate of product demands; and, when data on purchase decisions or market shares are available, to infer consumers' preferences over observed product characteristics. These models also serve as a building block in modeling firms' pricing and assortment optimization problems. We consider a firm's multiproduct pricing problem, in which product demands are determined by a pure characteristics model. A sample average approximation (SAA) method is used to approximate the expected market share of products and the firm profit. We propose an SAA-regularized method for the multiproduct price optimization problem. We present convergence analysis and numerical examples to show the efficiency and the effectiveness of the proposed method. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Mathematical programming, Sept. 2017, v. 165, no. 1, p. 361-389 | en_US |
dcterms.isPartOf | Mathematical programming | en_US |
dcterms.issued | 2017-09 | - |
dc.identifier.isi | WOS:000411225100010 | - |
dc.identifier.eissn | 1436-4646 | en_US |
dc.identifier.rosgroupid | 2017000113 | - |
dc.description.ros | 2017-2018 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.validate | 201805 bcrc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | AMA-0470 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6734047 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Chen_Saa-Regularized_Methods_Multiproduct.pdf | Pre-Published version | 838.75 kB | Adobe PDF | View/Open |
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