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EVOW
2008
Springer
15 years 6 months ago
A Memory Enhanced Evolutionary Algorithm for Dynamic Scheduling Problems
Abstract. This paper describes a memory enhanced evolutionary algorithm (EA) approach to the dynamic job shop scheduling problem. Memory enhanced EAs have been widely investigated ...
Gregory J. Barlow, Stephen F. Smith
MEMETIC
2010
311views more  MEMETIC 2010»
14 years 11 months ago
Iterated local search with Powell's method: a memetic algorithm for continuous global optimization
In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization proces...
Oliver Kramer
BMCBI
2004
181views more  BMCBI 2004»
15 years 4 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
IWPEC
2009
Springer
15 years 11 months ago
Paths of Bounded Length and Their Cuts: Parameterized Complexity and Algorithms
We study the parameterized complexity of two families of problems: the bounded length disjoint paths problem and the bounded length cut problem. From Menger’s theorem both proble...
Petr A. Golovach, Dimitrios M. Thilikos
GECCO
2000
Springer
156views Optimization» more  GECCO 2000»
15 years 8 months ago
Optimal Mutation Rates and Selection Pressure in Genetic Algorithms
It has been argued that optimal per-locus mutation rates in GAs are proportional to selection pressure and the reciprocal of genotype length. In this paper we suggest that the not...
Gabriela Ochoa, Inman Harvey, Hilary Buxton