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EMO
2001
Springer
107views Optimization» more  EMO 2001»
14 years 4 days ago
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Joshua D. Knowles, Richard A. Watson, David Corne
EVOW
2004
Springer
14 years 1 months ago
Improving Edge Recombination through Alternate Inheritance and Greedy Manner
Genetic Algorithms (GAs) are well-known heuristic algorithms and have been widely applied to solve combinatorial problems. Edge recombination is one of the famous crossovers design...
Chuan-Kang Ting
FOCS
2003
IEEE
14 years 28 days ago
Approximation Algorithms for Asymmetric TSP by Decomposing Directed Regular Multigraphs
A directed multigraph is said to be d-regular if the indegree and outdegree of every vertex is exactly d. By Hall’s theorem one can represent such a multigraph as a combination ...
Haim Kaplan, Moshe Lewenstein, Nira Shafrir, Maxim...
BMCBI
2008
166views more  BMCBI 2008»
13 years 7 months ago
Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...
AAAI
1998
13 years 9 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies