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SIAMJO
2008
57views more  SIAMJO 2008»
13 years 10 months ago
Universal Confidence Sets for Solutions of Optimization Problems
We consider random approximations to deterministic optimization problems. The objective function and the constraint set can be approximated simultaneously. Relying on concentratio...
Silvia Vogel
GECCO
2007
Springer
289views Optimization» more  GECCO 2007»
14 years 4 months ago
A discrete particle swarm optimization algorithm for the generalized traveling salesman problem
Dividing the set of nodes into clusters in the well-known traveling salesman problem results in the generalized traveling salesman problem which seeking a tour with minimum cost p...
Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan,...
ESA
2009
Springer
109views Algorithms» more  ESA 2009»
14 years 4 months ago
Iterative Rounding for Multi-Objective Optimization Problems
In this paper we show that iterative rounding is a powerful and flexible tool in the design of approximation algorithms for multiobjective optimization problems. We illustrate tha...
Fabrizio Grandoni, R. Ravi, Mohit Singh
FLAIRS
2006
13 years 11 months ago
Genetic Programming: Analysis of Optimal Mutation Rates in a Problem with Varying Difficulty
In this paper we test whether a correlation exists between the optimal mutation rate and problem difficulty. We find that the range of optimal mutation rates is inversely proporti...
Alan Piszcz, Terence Soule
HEURISTICS
2006
197views more  HEURISTICS 2006»
13 years 10 months ago
Bucket elimination for multiobjective optimization problems
Multiobjective optimization deals with problems involving multiple measures of performance that should be optimized simultaneously. In this paper we extend bucket elimination (BE),...
Emma Rollon, Javier Larrosa