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 more traditional partitioning methods as well as the superior scalability of nagging to larger numbers of processors
An Optimal Multiprocessor Combinatorial Auction Solver
Codenotti B
2009
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 more traditional partitioning methods as well as the superior scalability of nagging to larger numbers of processorsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.