Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
474841 | Computers & Operations Research | 2009 | 18 Pages |
Abstract
A combinatorial auction (CA) is an auction that permits bidders to bid on bundles of goods rather than just a single item. Unfortunately, winner determination for CAs is known to be NP-hard. In this paper, we propose a distributed algorithm to compute optimal solutions to this problem. The algorithm uses nagging, a technique for parallelizing search in heterogeneous distributed computing environments. Here, we show how nagging can be used to parallelize a branch-and-bound algorithm for this problem, and provide empirical results supporting both the performance advantage of nagging over more traditional partitioning methods as well as the superior scalability of nagging to larger numbers of processors.
Related Topics
Physical Sciences and Engineering
Computer Science
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Authors
Shouxi Yang, Alberto Maria Segre, Bruno Codenotti,