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An Inverse-Optimization-Based Auction Mechanism to Support a Multi-Attribute Rfq Process (Classic Reprint) - Hardcover

 
9780484461313: An Inverse-Optimization-Based Auction Mechanism to Support a Multi-Attribute Rfq Process (Classic Reprint)

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Excerpt from An Inverse-Optimization-Based Auction Mechanism to Support a Multi-Attribute Rfq Process

To engage bidders in a multi - attribute auction, an auctioneer needs to provide the bidders with some information pertaining to how he values the non-price attributes. While several rather obtuse approaches are possible the auctioneer could provide shadow prices from a mathematical program without revealing the mathematical program), the predominant approach in hpo practice and the one favored by most bidders because of its straightforward nature is for the auctioneer to announce a scoring rule in terms of the bid price and various attributes. This scoring rule may, or may not, be identical to the auctioneer's true utility function; indeed, this is the crux of the strategic problem from the auctioneer's viewpoint.

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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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Excerpt from An Inverse-Optimization-Based Auction Mechanism to Support a Multi-Attribute Rfq Process

We consider a manufacturer who uses a reverse, or procurement, auction to determine which supplier will be awarded a contract. Each bid consists of a price and a set of non-price attributes (e.g., quality, lead time). The manufacturer is assumed to know the parametric form of the suppliers' cost functions (in terms of the non-price attributes), but has no prior information on the parameter values. We construct a multi-round open-ascending auction mechanism, where the manufacturer announces a slightly different scoring rule (i.e., a function that ranks the bids in terms of the price and non-price attributes) in each round. Via inverse optimization, the manufacturer uses the bids from the first several rounds to learn the suppliers' cost functions, and then in the final round chooses a scoring rule that attempts to maximize his own utility. Under the assumption that suppliers submit their myopic best-response bids in the last round, and do not distort their bids in the earlier rounds (i.e., they choose their minimum-cost bid to achieve any given score), our mechanism indeed maximizes the manufacturers utility within the open-ascending format. We also discuss several enhancements that improve the robustness of our mechanism with respect to the models informational and behavioral assumptions.

About the Publisher

Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com

This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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  • VerlagForgotten Books
  • Erscheinungsdatum2018
  • ISBN 10 0484461311
  • ISBN 13 9780484461313
  • EinbandTapa dura
  • SpracheEnglisch
  • Anzahl der Seiten120
  • Kontakt zum HerstellerNicht verfügbar

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Lawrence M. Wein
Verlag: Forgotten Books, 2018
ISBN 10: 0484461311 ISBN 13: 9780484461313
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