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72
The Crossover Landscape for the Onemax Problem
, 1996
"... In seeking to understand how and why genetic algorithms (GAs) work, attention has been focussed on the landscapes on which they search. While it is relatively simple to analyse the landscapes induced by traditional neighbourhood search operators, the position is considerably complicated for the oper ..."
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Cited by 10 (0 self)
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for the operators normally used by a GA. Problems which have a single global optimum on a standard `Hamming' landscape such as the familiar Onemax function actually possess an exponentially increasing number of local optima on the landscape associated with crossover. Nevertheless, GAs can solve such problems
Variable Length Genetic Algorithms with Multiple Chromosomes on a Variant of the Onemax Problem Investigating Changes in Chromosome Length
"... The dynamics of variable length representations in evolutionary computation have been shown to be complex and different from those seen in standard fixed length genetic algorithms. This paper explores a simple variable length genetic algorithm with multiple chromosomes and its underlying dynamics wh ..."
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when used for the onemax problem. The changes in length of the chromosomes are especially observed and explanations for these fluctuations are sought.
Population Sizing for Optimum Sampling with Genetic Algorithms: A Case Study of the Onemax Problem
, 1998
"... An experimental and analytical investigation of sampling, which focused on the sizing of population for optimum performance, was performed using the OneMax problem. A fixedsize population and population sizes that vary according to the number of samples were considered in this study. For the ..."
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Cited by 11 (1 self)
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An experimental and analytical investigation of sampling, which focused on the sizing of population for optimum performance, was performed using the OneMax problem. A fixedsize population and population sizes that vary according to the number of samples were considered in this study
A Design for DNA Computation of the OneMax Problem
, 2001
"... Elements of evolutionary computation and molecular biology are combined to design a DNA evolutionary computation. The traditional test problem for evolutionary computation, OneMax problem is addressed. The key feature is the physical separation of DNA strands consistent with OneMax "fitne ..."
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Cited by 4 (1 self)
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Elements of evolutionary computation and molecular biology are combined to design a DNA evolutionary computation. The traditional test problem for evolutionary computation, OneMax problem is addressed. The key feature is the physical separation of DNA strands consistent with OneMax "fitness."
The Role of Neutral and Adaptive Mutation in an Evolutionary Search on the OneMax Problem
 Blackwell Science Ltd, Global Change Biology
, 2002
"... We investigate neutrality in the simple Genetic Algorithms (SGA) and in our neutralityenabled evolutionary system using the OneMax problem. ..."
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Cited by 9 (0 self)
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We investigate neutrality in the simple Genetic Algorithms (SGA) and in our neutralityenabled evolutionary system using the OneMax problem.
Optimal Sampling and Speedup for Genetic Algorithms on the Sampled OneMax Problem
, 2003
"... This paper investigates the optimal sampling and the speedup obtained through sampling for the sampled OneMax problem. Theoretical and experimental analyses are given for three di#erent populationsizing models: the decisionmaking model, the gambler's ruin model, and the fixed populations ..."
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Cited by 6 (2 self)
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This paper investigates the optimal sampling and the speedup obtained through sampling for the sampled OneMax problem. Theoretical and experimental analyses are given for three di#erent populationsizing models: the decisionmaking model, the gambler's ruin model, and the fixed population
Evolution Strategies, Network Random Keys, and the OneMax Tree Problem
 In Applications of Evolutionary Computing: EvoWorkshops, Edited by Stefano Cagnoni, Jens
, 2002
"... Evolution strategies (ES) are efficient optimization methods for continuous problems. However, many combinatorial optimization methods can not be represented by using continuous representations. The development of the network random key representation which represents trees by using real numbers ..."
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Cited by 7 (0 self)
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Evolution strategies (ES) are efficient optimization methods for continuous problems. However, many combinatorial optimization methods can not be represented by using continuous representations. The development of the network random key representation which represents trees by using real
Climbing Unimodal Landscapes with Neutrality: A Case Study of the OneMax Problem
"... We investigate fitness neutrality in a Simple Evolutionary Algorithm (SEA) and in a neutralityenabled evolutionary system using the OneMax problem. The results show that with the support of limited neutrality, SEA is less effective than our system where a larger amount of neutrality is supported. I ..."
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We investigate fitness neutrality in a Simple Evolutionary Algorithm (SEA) and in a neutralityenabled evolutionary system using the OneMax problem. The results show that with the support of limited neutrality, SEA is less effective than our system where a larger amount of neutrality is supported
Evolution Strategies Random Network Keys and the OneMax Tree Problem
, 2001
"... Evolution strategies (ES) are efficient optimization methods for continuous problems. How ever, many combinatorial optimization methods can not be represented by using continuous representations. The development of the network random key representation (Rothlauf et al., 2000) which represents tr ..."
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Evolution strategies (ES) are efficient optimization methods for continuous problems. How ever, many combinatorial optimization methods can not be represented by using continuous representations. The development of the network random key representation (Rothlauf et al., 2000) which represents
In Vitro Selection for a OneMax DNA Evolutionary Computation
 DIMACS SERIES IN DISCRETE MATHEMATICS AND THEORETICAL COMPUTER SCIENCE
"... Aspects of Evolutionary Computation, DNA computing, and in vitro evolution are combined in proposed laboratory procedures. Preliminary experimental results are shown. The traditional test problem for Evolutionary Computation known as the OneMax problem is addressed. The preliminary experimental resu ..."
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Cited by 3 (2 self)
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Aspects of Evolutionary Computation, DNA computing, and in vitro evolution are combined in proposed laboratory procedures. Preliminary experimental results are shown. The traditional test problem for Evolutionary Computation known as the OneMax problem is addressed. The preliminary experimental
Results 1  10
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72