An optimal multiprocessor combinatorial auction solver

Computers and Operations Research

Volumn 36, Issue 1, 2009, Pages 149-166

  Yang, Shouxi ^a   Segre, Alberto Maria ^a   Codenotti, Bruno ^b  

^a University of Iowa   (United States)

^b Istituto di informatica e telematica del Consiglio nazionale delle ricerche   (Italy)

Author keywords

Branch and bound; Combinatorial auctions; Nagging; Parallel computing; Winner determination

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; CALCIUM; COMPUTATIONAL METHODS; COMPUTER SYSTEMS; EVOLUTIONARY ALGORITHMS; MULTITASKING; NUCLEAR PROPULSION; NUMBER THEORY; NUMERICAL METHODS; SCHEDULING ALGORITHMS;

COMBINATORIAL AUCTIONS; DISTRIBUTED ALGORITHMS; DISTRIBUTED COMPUTING; ELSEVIER (CO); EMPIRICAL RESULTS; NP-HARD; OPTIMAL SOLUTIONS; PARALLELIZING; PARTITIONING METHODS; WINNER DETERMINATION;

PARALLEL ALGORITHMS;

EID: 44849129211     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2007.08.001     Document Type: Article

References (30)

1. Rassenti S.J., Smith V.L., and Bulfin R.L. A combinatorial auction mechanism for airport time slot allocation. Bell Journal of Economics 13 2 (1982) 402-417
2. Nisan N. Bidding and allocation in combinatorial auctions. Proceedings of the second association for computing machinery conference on electronic commerce (EC00) (2000) 1-12
3. Rothkopf MH, Pekec A, Harstad RM. Computationally manageable combinatorial auctions. Technical Report 95-09, DIMACS, Rutgers, NJ, 1995.
4. Sandholm T. An algorithm for optimal winner determination in combinatorial auctions. Proceedings of the 16th international joint conference on artificial intelligence (IJCAI99) (1999) 542-547
5. Segre A.M., Forman S., Resta G., and Wildenberg A. Nagging: a scalable, fault-tolerant, distributed search paradigm. Artificial Intelligence 140 1-2 (2002) 71-106
6. Leyton-Brown K., Shoham Y., and Tennenholtz M. An algorithm for multi-unit combinatorial auctions. Proceedings of the 17th national conference on artificial intelligence and 12th conference on innovative applications of artificial intelligence (2000) 56-61
7. Sandholm T., and Suri S. BOB: improved winner determination in combinatorial auctions and generalizations. Artificial Intelligence 145 1-2 (2003) 33-58
8. de Vries S, Vohra R. Combinatorial auctions: a survey, Technical Report 1296, Center for Mathematical Studies in Economics and Management Science, Northwestern University, Evanston, IL, 2000.
9. Gonen R., and Lehmann D. Optimal solutions for multi-unit combinatorial auctions: branch and bound heuristics. Proceedings of the second association for computing machinery conference on electronic commerce (EC00) (2000) 13-20
10. Fujishima Y., Leyton-Brown K., and Shoham Y. Taming the computational complexity of combinatorial auctions: optimal and approximate approaches. Proceedings of the 16th international joint conference on artificial intelligence (IJCAI99) (1999) 548-553
11. Hoos H.H., and Boutilier C. Solving combinatorial auctions using stochastic local search. Proceedings of the 17th national conference on artificial intelligence and 12th conference on innovative applications of artificial intelligence (2000) 22-29
12. Lehmann D, O'Callaghan LI, Shoham Y. Truth revelation in rapid, approximately efficient combinatorial auctions. CS-TN-99-88, Stanford University, Palo Alto, CA; 1999.
13. Zurel E., and Nisan N. An efficient approximate allocation algorithm for combinatorial auctions. Proceedings of the third association for computing machinery conference on electronic commerce (EC01) (2001) 125-136
14. Andersson A., Tenhunen M., and Ygge F. Integer programming for combinatorial auction winner determination. Proceedings of the fourth international conference on multiagent systems (ICMAS 2000). Institute of Electrical and Electronics Engineers Computer Society (2000) p. 39
15. Nilsson N. Problem-solving methods in artificial intelligence (1971), McGraw-Hill, New York, NY
16. Lam W., and Segre A.M. A parallel learning algorithm for Bayesian inference networks. IEEE Transactions on Knowledge and Data Engineering 14 1 (2002) 93-105
17. Segre A.M., and Sturgill D.B. Using hundreds of workstations to solve first-order logic problems. Proceedings of the 12th national conference on artificial intelligence (1994) 187-192
18. Sturgill D.B., and Segre A.M. Nagging: a distributed adversarial search-pruning technique applied to first-order logic. Journal of Automated Reasoning 19 3 (1997) 347-376
19. Sturgill D.B., and Segre A.M. A novel asynchronous parallelization scheme for first-order logic. Proceedings of the 12th conference on automated deduction (1994) 484-498
20. Beguelin A., Dongarra J., Jiang W., Manchek R., and Sunderam V. PVM users guide and reference manual (May 1994), Oak Ridge National Laboratory, Oak Ridge, TN
21. Gropp W., Lusk E., Doss N., and Skjellum A. A high-performance, portable implementation of the MPI message-passing interface standard. Parallel Computing 22 6 (1996) 789-828
22. Leyton-Brown K., Pearson M., and Shoham Y. Towards a universal test suite for combinatorial auction algorithms. Proceedings of the second association for computing machinery conference on electronic commerce (EC00) (2000) 66-76
23. Bonaccorsi A., Codenotti B., Dimitri N., Leoncini M., Resta G., and Santi P. Generating realistic data sets for combinatorial auctions. Institute of electrical and electronics engineers international conference on e-commerce (June 2003) 331-338
24. Fleming P.J., and Wallace J.J. How not to lie with statistics: the correct way to summarize benchmark results. Communications of the Association for Computing Machinery 29 3 (1986) 219-221
25. Smith J.E. Characterizing computer performance with a single number. Communications of the Association for Computing Machinery 32 10 (1988) 1202-1206
26. Segre A.M., Elkan C.P., and Russell A. A critical look at experimental evaluations of EBL. Machine Learning 6 2 (1991) 183-196
27. Wilcoxon F. Individual comparisons by ranking methods. Biometrics 1 (1945) 80-83
28. Gonen R., and Lehmann D. Linear programming helps solving large multi-unit combinatorial auctions. Proceedings of the electronic market design workshop (2001)
29. Forman S., and Segre A.M. NAGSAT: a randomized, complete, parallel solver for 3SAT. Fifth international symposium on the theory and applications of satisfiability testing (May 2002) 236-243
30. Liu Y., Segre A.M., and Wang S. A high throughput approach to combinatorial search on grids (poster). 15th IEEE international symposium on high performance distributed computing (June 2006)