Multi-chromosomes representations have been used in Genetic Algorithms to decompose complex solution representations into simpler components each of which is represented onto a single chromosome. This paper investigates the effects of distributing similar structures over a number of chromosomes. The solution representation of a simple mixed integer problem is encoded onto one, two, or three chromosomes to measure the effects. Initial results showed large differences, but further investigation showed that most of the differences were due to increased mutation, but multi-chromosome representation can give superior results
The past thirty years have seen a rapid growth in the popularity and use of Genetic Algorithms for s...
Background: Next generation sequencing (NGS) technologies have made it possible to exhaustively dete...
This article introduces the concept of variable chromosome lengths in the context of an adaptive gen...
. Multi-chromosomes representations have been used in Genetic Algorithms to decompose complex soluti...
A multi-chromosome GA (Multi-GA) was developed, based upon concepts from the natural world, allowing...
Linear Genetic Programming (LGP) is a Genetic Programming variant that uses linear chromosomes for ...
Self-adaptation is one of the most promising areas of research in evolutionary computation as it ada...
Optimization is essential for nding suitable answers to real life problems. In particular, genetic (...
Combinatorial optimisation problems are in the domain of Genetic Algorithms (GA) interest. Unfortuna...
We investigate different genetic algorithm and genetic programming variants of representation, decod...
Optimization is essential for nding suitable answers to real life problems. In particular, genetic (...
Abstract. This paper examines the effect of mimicking discontinuous heredity caused by carrying more...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
<p>Each chromosome found in the population formed in the GA is structurally an equal-length coded se...
Many phenotypes such as genetic disorders may be hereditary while others may be influenced by the en...
The past thirty years have seen a rapid growth in the popularity and use of Genetic Algorithms for s...
Background: Next generation sequencing (NGS) technologies have made it possible to exhaustively dete...
This article introduces the concept of variable chromosome lengths in the context of an adaptive gen...
. Multi-chromosomes representations have been used in Genetic Algorithms to decompose complex soluti...
A multi-chromosome GA (Multi-GA) was developed, based upon concepts from the natural world, allowing...
Linear Genetic Programming (LGP) is a Genetic Programming variant that uses linear chromosomes for ...
Self-adaptation is one of the most promising areas of research in evolutionary computation as it ada...
Optimization is essential for nding suitable answers to real life problems. In particular, genetic (...
Combinatorial optimisation problems are in the domain of Genetic Algorithms (GA) interest. Unfortuna...
We investigate different genetic algorithm and genetic programming variants of representation, decod...
Optimization is essential for nding suitable answers to real life problems. In particular, genetic (...
Abstract. This paper examines the effect of mimicking discontinuous heredity caused by carrying more...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
<p>Each chromosome found in the population formed in the GA is structurally an equal-length coded se...
Many phenotypes such as genetic disorders may be hereditary while others may be influenced by the en...
The past thirty years have seen a rapid growth in the popularity and use of Genetic Algorithms for s...
Background: Next generation sequencing (NGS) technologies have made it possible to exhaustively dete...
This article introduces the concept of variable chromosome lengths in the context of an adaptive gen...