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GECCO
1999
Springer
126views Optimization» more  GECCO 1999»
14 years 8 days ago
Improving Genetic Algorithms by Search Space Reductions (with Applications to Flow Shop Scheduling)
Crossover operators that preserve common components can also preserve representation level constraints. Consequently, these constraints can be used to beneficially reduce the sea...
Stephen Y. Chen, Stephen F. Smith
SAC
2004
ACM
14 years 1 months ago
A comparison of randomized and evolutionary approaches for optimizing base station site selection
It is increasingly important to optimally select base stations in the design of cellular networks, as customers demand cheaper and better wireless services. From a set of potentia...
Larry Raisanen, Roger M. Whitaker, Steve Hurley
SPDP
1991
IEEE
13 years 11 months ago
Asynchronous parallel search by the parallel genetic algorithm
The parallel genetic algorithm (PGA) is a prototype of a new kind of a distributed algorithm. It is based on a parallel search by individuals all of which have the complete proble...
Heinz Mühlenbein
EVOW
2010
Springer
14 years 2 months ago
Enhancing Genetic Algorithms by a Trie-Based Complete Solution Archive
Genetic algorithms (GAs) share a common weakness with most other metaheuristics: Candidate solutions are in general revisited multiple times, lowering diversity and wasting preciou...
Günther R. Raidl, Bin Hu
WABI
2005
Springer
117views Bioinformatics» more  WABI 2005»
14 years 1 months ago
Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons
Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal ali...
Pankaj K. Agarwal, Yonatan Bilu, Rachel Kolodny