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FOCS
2004
IEEE
14 years 13 days ago
Approximating the Stochastic Knapsack Problem: The Benefit of Adaptivity
We consider a stochastic variant of the NP-hard 0/1 knapsack problem in which item values are deterministic and item sizes are independent random variables with known, arbitrary d...
Brian C. Dean, Michel X. Goemans, Jan Vondrá...
APPROX
2008
Springer
124views Algorithms» more  APPROX 2008»
13 years 10 months ago
Deterministic 7/8-Approximation for the Metric Maximum TSP
We present the first 7/8-approximation algorithm for the maximum traveling salesman problem with triangle inequality. Our algorithm is deterministic. This improves over both the r...
Lukasz Kowalik, Marcin Mucha
LATIN
2010
Springer
13 years 10 months ago
Randomized Truthful Algorithms for Scheduling Selfish Tasks on Parallel Machines
We study the problem of designing truthful algorithms for scheduling a set of tasks, each one owned by a selfish agent, to a set of parallel (identical or unrelated) machines in or...
Eric Angel, Evripidis Bampis, Nicolas Thibault
ICALP
2010
Springer
14 years 1 months ago
Network Design via Core Detouring for Problems without a Core
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...
Fabrizio Grandoni, Thomas Rothvoß
CEC
2008
IEEE
14 years 3 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...