A genetic algorithm has been applied to optimizing a university class schedule. A complete description of the algorithm is beyond the scope of this paper, which will address the adaptive controls applied to the progress of the Genetic Algorithm. The benefits of dynamic operator selection in the genetic processes of child creation are described. A dynamic penalty function also guides the fitness and population selection of better-fit solutions. These adaptive controls are not inclusive of all possible adaptations but only hint at the improvements that can be achieved by using dynamic controls
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper presents Genetic-based learning Algorithms (GA) for automatically inducing control rules ...
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks su...
In this paper two methods for evolutionary algorithm control are proposed. The first one is a new me...
This paper investigates a methodology for adaptation of the mutation factor within an evolutionary a...
This paper presents a new approach of genetic algorithm (GA) to solve the constrained optimization p...
Abstract: Genetic algorithms are search and optimization techniques which have their origin and insp...
[[abstract]]According to the results of previous research, the genetic algorithm (GA) is a good tech...
Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance an...
Traditional artificial intelligence and computer-aided course scheduling schemes can no longer meet ...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of c...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks su...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper presents Genetic-based learning Algorithms (GA) for automatically inducing control rules ...
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks su...
In this paper two methods for evolutionary algorithm control are proposed. The first one is a new me...
This paper investigates a methodology for adaptation of the mutation factor within an evolutionary a...
This paper presents a new approach of genetic algorithm (GA) to solve the constrained optimization p...
Abstract: Genetic algorithms are search and optimization techniques which have their origin and insp...
[[abstract]]According to the results of previous research, the genetic algorithm (GA) is a good tech...
Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance an...
Traditional artificial intelligence and computer-aided course scheduling schemes can no longer meet ...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of c...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks su...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
Genetic algorithms, which were created on the basis of observation and imitation of processes happen...
This paper presents Genetic-based learning Algorithms (GA) for automatically inducing control rules ...
The paper concerns the application of Genetic Algorithms and Genetic Programming to complex tasks su...