TitleStochastic analysis of bidding in sequential auctions and related problems
NamePuranam, Srinivasa Kartikeya (author), Katehakis, Michael N (chair), Armstrong, Ronald (internal member), Melamed, Benjamin (internal member), Xu, Xiaowei (internal member), Sheshadri, Sridhar (outside member), Zhou, Bin (outside member), Rutgers University, Graduate School - Newark,
DescriptionIn this thesis we study bidding in sequential auctions and taboo optimiza- tion criteria for Markov Decision Processes. In the second chapter we study the problem of sequentially bidding in N auctions of identical items. It is assumed that at each auction there is a sufficiently high price that if paid the item is won. The objective is to acquire a fixed number of these items at a minimum expected cost. In the third chapter we consider the problem of a firm (“the bidder”) that in each period, of an infinite time horizon, buys items in auctions and sells the acquired items in a secondary market. We investigate optimal bidding strategies for the bidder that take into account the cost of acquiring the items, the random sale price and demand of the sec- ondary market as well as pertinent salvage value or inventory holding costs. In the final chapter we consider Markovian systems where costs or rewards are unknown either in some states or in all states. For such cases we define taboo optimization criteria for a propitiously defined set of taboo states.
NoteIncludes bibliographical references
Noteby Srinivasa Kartikeya Puranam
CollectionGraduate School - Newark Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.