The author has conducted research mainly into the use of genetic algorithm as a problem solving method applied to scheduling and combinational problem. A main feature of both kinds of problems is that their research objects do not permit multiple selection, therefore genetic manipulation has been carried out using order expression. However, when crossover and mutation are carried out in the order expression this breaks the good gene sequence from the previous generation. Therefore crossover and mutation do not necessarily produce a very good individual. In another paper a different method called the sub tour crossover method was proposed. This method makes it possible to preserve the genotype as the genetic expression, therefore allowing th...
The paper provides an improved evolutionary strategy (ES) of genetic algorithm (GA) on the basis of ...
For more than two decades, genetic algorithms (GAs) have been studied by researchers from different ...
In this paper, we propose a selective mutation method for improving the performances of genetic algo...
In the Bulletin of Niigata University of International and Information Studies [No.4], I proposed th...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
This paper presents some experimental results and analyses of the gene invariant genetic algorithm(G...
It is well known that a judicious choice of crossover and/or mutation rates is critical to the succe...
This paper presents a large and systematic body of data on the relative effectiveness of mutation, c...
Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Char...
Genetic algorithms (GAs) are dependent on various operators and parameters. The most common evolutio...
ABSTRACT Genetic Algorithms (GAs) are a set of local search algorithms that are based on principles ...
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level ...
The genetic algorithm (GA) is an optimization and search technique based on the principles of geneti...
Abstract. a new genetic algorithm is proposed in the paper. Different from other genetic algorithms,...
Abstract — Genetic algorithm (GA), as an important intelligence computing tool, is a wide research c...
The paper provides an improved evolutionary strategy (ES) of genetic algorithm (GA) on the basis of ...
For more than two decades, genetic algorithms (GAs) have been studied by researchers from different ...
In this paper, we propose a selective mutation method for improving the performances of genetic algo...
In the Bulletin of Niigata University of International and Information Studies [No.4], I proposed th...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
This paper presents some experimental results and analyses of the gene invariant genetic algorithm(G...
It is well known that a judicious choice of crossover and/or mutation rates is critical to the succe...
This paper presents a large and systematic body of data on the relative effectiveness of mutation, c...
Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Char...
Genetic algorithms (GAs) are dependent on various operators and parameters. The most common evolutio...
ABSTRACT Genetic Algorithms (GAs) are a set of local search algorithms that are based on principles ...
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level ...
The genetic algorithm (GA) is an optimization and search technique based on the principles of geneti...
Abstract. a new genetic algorithm is proposed in the paper. Different from other genetic algorithms,...
Abstract — Genetic algorithm (GA), as an important intelligence computing tool, is a wide research c...
The paper provides an improved evolutionary strategy (ES) of genetic algorithm (GA) on the basis of ...
For more than two decades, genetic algorithms (GAs) have been studied by researchers from different ...
In this paper, we propose a selective mutation method for improving the performances of genetic algo...