Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Average-case analysis of off-line and on-line knapsack problems
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Scheduling jobs before shut-down
Nordic Journal of Computing
Scheduling Jobs Before Shut-Down
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
Random knapsack in expected polynomial time
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Probabilistic analysis of knapsack core algorithms
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Computing equilibria for congestion games with (im)perfect information
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Typical properties of winners and losers in discrete optimization
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Random knapsack in expected polynomial time
Journal of Computer and System Sciences - Special issue: STOC 2003
Development of core to solve the multidimensional multiple-choice knapsack problem
Computers and Industrial Engineering
Pareto optimal solutions for smoothed analysts
Proceedings of the forty-third annual ACM symposium on Theory of computing
Smoothed analysis of integer programming
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Smoothed analysis of integer programming
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Guarantees for the success frequency of an algorithm for finding dodgson-election winners
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Average-case analysis of a greedy algorithm for the 0/1 knapsack problem
Operations Research Letters
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Given a 0-1 knapsack problem with input drawn from a certain probability distribution, we show that for every &egr; 0, there is a self-checking polynomial-time algorithm that finds an optimal solution with probability at least 1 -&egr;. We also prove some upper and lower bounds on random variables related to the problem.