SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An approximate truthful mechanism for combinatorial auctions with single parameter agents
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Approximation Schemes for Covering and Scheduling on Related Machines
APPROX '98 Proceedings of the International Workshop on Approximation Algorithms for Combinatorial Optimization
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
Truthful approximation mechanisms for restricted combinatorial auctions: extended abstract
Eighteenth national conference on Artificial intelligence
Strategyproof cost-sharing mechanisms for set cover and facility location games
Proceedings of the 4th ACM conference on Electronic commerce
Truthful Mechanisms for One-Parameter Agents
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
ACM SIGecom Exchanges
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Fast monotone 3-approximation algorithm for scheduling related machines
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Truthful approximation mechanisms for scheduling selfish related machines
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
A polynomial-time approximation scheme for maximizing the minimum machine completion time
Operations Research Letters
Maximizing the Minimum Load: The Cost of Selfishness
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Truthful Approximation Schemes for Single-Parameter Agents
SIAM Journal on Computing
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We consider the problem of maximizing the minimum load for machines that are controlled by selfish agents, who are only interested in maximizing their own profit. Unlike the classical load balancing problem, this problem has not been considered for selfish agents until now. For a constant number of machines, m, we show a monotone polynomial time approximation scheme (PTAS) with running time that is linear in the number of jobs. It uses a new technique for reducing the number of jobs while remaining close to the optimal solution. We also present an FPTAS for the classical problem, i.e., where no selfish agents are involved (the previous best result for this case was a PTAS) and use this to give a monotone FPTAS. Additionally, we give a monotone approximation algorithm with approximation ratio min(m, (2 + Ɛ)s1/sm) where Ɛ 0 can be chosen arbitrarily small and si is the (real) speed of machine i. Finally we give improved results for two machines.