Title :
Generating realistic data sets for combinatorial auctions
Author :
Bonaccorsi, A. ; Codenotti, B. ; Dimitri, N. ; Leoncini, M. ; Resta, G. ; Santi, P.
Author_Institution :
Scuola Superiore S. Anna, Pisa, Italy
Abstract :
We consider the generation of realistic data sets for combinatorial auctions. This problem has been recognized as central to enhance the contribution of the computer science community to the field. We put forward the notions of structure and budget as main guidelines towards the generation of succinct and realistic input data. We describe a computational framework for the analysis of existing algorithms against realistic benchmarks, and use it in the context of two real world scenarios, i.e., real estate and railroad track auctions. The results of this analysis suggest that the obstacles to using (one round) combinatorial auctions in real world applications might be of an economic nature rather than a computational one.
Keywords :
budgeting; electronic money; electronic trading; performance evaluation; real estate data processing; algorithm analysis; approximation algorithms; auction coverage; budget; combinatorial auction; computational framework; computer science community contribution; economic nature; railroad track auction; real estate auction; real world scenario; realistic benchmark; realistic data set generation; realistic input data generation; revenue optimality; structure; succinct input data generation; Algorithm design and analysis; Application software; Computer science; Consumer products; Cost accounting; Frequency; Guidelines; Marketing and sales; Power generation economics; Testing;
Conference_Titel :
E-Commerce, 2003. CEC 2003. IEEE International Conference on
Print_ISBN :
0-7695-1969-5
DOI :
10.1109/COEC.2003.1210268