USING AN ANALYTIC NETWORK PROCESS MODEL IN COMBINATORIAL AUCTIONS

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Published Dec 23, 2009
Petr Fiala

Abstract

Auctions are important market mechanisms for the allocation of goods and services. Auctions are preferred often to other common processes because they are open, quite fair, easiness to understand by participants, and lead to economically efficient outcomes. Design of auctions is a multidisciplinary effort made of contributions from economics, operations research, informatics, and other disciplines. Combinatorial auctions are those auctions in which bidders can place bids on combinations of items, called packages, rather than just individual items. The advantage of combinatorial auctions is that the bidder can more fully express his preferences. This is particular important when items are complements. The multiple evaluation criteria can be used. There are dependencies among sellers, buyers, criteria, bundles of items. A variety of feedback processes creates complex system of items. For the whole structure seems to be very appropriate Analytic Network Process (ANP) approach. The ANP method makes possible to deal systematically with all kinds of dependence and feedback in the system of items. By the ANP approach can be evaluated the preferences of bundles of items. Dynamic Network Process (DNP) as an extension of ANP can deal with time dependent priorities in combinatorial auctions.

http://dx.doi.org/10.13033/ijahp.v1i2.47

How to Cite

Fiala, P. (2009). USING AN ANALYTIC NETWORK PROCESS MODEL IN COMBINATORIAL AUCTIONS. International Journal of the Analytic Hierarchy Process, 1(2). https://doi.org/10.13033/ijahp.v1i2.47

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Keywords

combinatorial auctions, preference elicitation, Analytic Network Process, Dynamic Network Process

References
Bellosta, M., Brigui, I., Kornman, S., & Vanderpooten, D. (2004). A multi-criteria model
for electronic auctions. ACM Symposium on Applied Computing, 759-765.
Bichler, M. (2000). An experimental analysis of multi-attribute auctions. Decision
Support Systems, 29, 249- 268.
Bikhchandani, S., & Ostroy, J.M. (2002). The package assignment model. Journal of
Economic Theory, 107, 377–406.
CDF (Creative Decisions Foundation) www page (2000)- www.creativedecisions.net.
Cramton, P., Shoham, Y., & Steinberg, R. (eds.) (2006). Combinatorial Auctions.
Cambridge, MIT Press.
de Vries, S., & Vohra, R.V. (2003). Combinatorial auctions: A survey. INFORMS
Journal of Computing, 15, 284-309,
Fiala, P. (2006). An ANP/DNP analysis of economic elements in today's world network
economy. Journal of Systems Science and Systems Engineering, 15, 131–140.
Fiala, P. (1997). Models of cooperative decision making. Gal, T., & Fandel, G. (eds.).
Multiple Criteria Decision Making, Heidelberg, Springer.
Oliveira, E., Fonsesca, J.M., & Steiger-Garao, A. (1999). Multi-criteria negotiation in
multi-agent systems. 1st International Workshop of Central and Eastern Europe on
Multi-agent Systems (CEEMAS'99), St. Petersburg.
Rothkopf, M., Peke?, A., & Harstad, R. (1998). Computationally manageable
combinational auctions. Management Science, 8, 1131-1147.
Saaty, T.L. (1996). The Analytic Hierarchy Process. Pittsburgh: RWS Publications.
Saaty, T.L. (2001). Decision making with Dependence and Feedback: The Analytic
Network Process. Pittsburgh: RWS Publications.
Saaty, T.L. (2003). Time Dependent Decision-Making; Dynamic Priorities in AHP/ANP:
Generalizing from Points to Functions and from Real to Complex Variables. Proceedings
of the 7th International Conference on the Analytic Hierarchy Process, Bali, Indonesia, 1-
38.
Sandholm, T. (2002). Algorithm for optimal winner determination in combinatorial
auctions. Artificial Intelligence, 135, 1-54.
Sandholm, T., & Boutilier, C. (2006). Preference elicitation in combinatorial auctions.
Cramton, P., Shoham, Y., & Steinberg, R. (eds.). Combinatorial Auctions. Cambridge,
MIT Press.
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