Using a Lagrangian Heuristic for a Combinatorial Auction Problem
Combinatorial auctions allow bidders to bid for items leading to more efficient allocations, but determining winners in auctions is $\mathcal{NP}$-complete. In this work, a simple yet effective Lagrangian relaxation based heuristic algorithm is presented. Extensive computational experiments using st...
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sg-smu-ink.lkcsb_research-15572016-03-12T07:10:29Z Using a Lagrangian Heuristic for a Combinatorial Auction Problem GUO, Yunsong LIM, Andrew RODRIGUES, Brian TANG, Jiqing Combinatorial auctions allow bidders to bid for items leading to more efficient allocations, but determining winners in auctions is $\mathcal{NP}$-complete. In this work, a simple yet effective Lagrangian relaxation based heuristic algorithm is presented. Extensive computational experiments using standard benchmark data (CATS) as well as newly generated more realistic test sets were conducted which showed the heuristic was able to provide optimal solutions for most test cases and is within 1% from the optimums for the rest within very short times. Experiements comparing CPLEX 8.0, the fastest current algorithm, showed the heuristic was able to provide equally godd or better solutions often requring less than 1% of the time required by CPLEX 8.0. 2006-07-01T07:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/558 info:doi/10.1142/S0218213006002771 https://doi.org/10.1142/S0218213006002771 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Combinatorial auction Langrange relaxation heuristic Operations and Supply Chain Management |
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Combinatorial auction Langrange relaxation heuristic Operations and Supply Chain Management GUO, Yunsong LIM, Andrew RODRIGUES, Brian TANG, Jiqing Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
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Combinatorial auctions allow bidders to bid for items leading to more efficient allocations, but determining winners in auctions is $\mathcal{NP}$-complete. In this work, a simple yet effective Lagrangian relaxation based heuristic algorithm is presented. Extensive computational experiments using standard benchmark data (CATS) as well as newly generated more realistic test sets were conducted which showed the heuristic was able to provide optimal solutions for most test cases and is within 1% from the optimums for the rest within very short times. Experiements comparing CPLEX 8.0, the fastest current algorithm, showed the heuristic was able to provide equally godd or better solutions often requring less than 1% of the time required by CPLEX 8.0. |
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GUO, Yunsong LIM, Andrew RODRIGUES, Brian TANG, Jiqing |
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GUO, Yunsong LIM, Andrew RODRIGUES, Brian TANG, Jiqing |
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GUO, Yunsong |
title |
Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
title_short |
Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
title_full |
Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
title_fullStr |
Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
title_full_unstemmed |
Using a Lagrangian Heuristic for a Combinatorial Auction Problem |
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using a lagrangian heuristic for a combinatorial auction problem |
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Institutional Knowledge at Singapore Management University |
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2006 |
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https://ink.library.smu.edu.sg/lkcsb_research/558 https://doi.org/10.1142/S0218213006002771 |
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