Over the last decade, variant of genetic algorithm (GA) approaches have been used to solve various type of optimization problems. Premature convergence is the main problem for GA performance. A common hyphothesis is that high diversity is important to avoid this problem. Failure to maintain GA population diversity will lead to this problem and affected quality of result will be produced. In this paper, we proposed two-problem representation and two strategies to retain population diversity as well as preventing premature convergence. The algorithm was then applied to timetabling problem and showed promising result
Population diversity is essential for avoiding premature convergence in Genetic Algorithms (GAs) and...
. Genetic algorithms are widely used as optimization and adaptation tools, and they became important...
Evolutionary Algorithms is one of the fastest growing areas of computer science. The simple Genetic ...
Abstract. Over the last decade, variant of genetic algorithm (GA) approaches have been used to solve...
This paper surveys strategies applied to avoid premature convergence in Genetic Algorithms (GAs).Gen...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Premature convergence in the process of genetic algorithm (GA) for searching solution is frequently ...
Genetic Algorithms (GA) is an evolutionary inspired heuristic search algorithm. Like all heuristic s...
Abstract — Genetic algorithm (GA), as an important intelligence computing tool, is a wide research c...
Genetic adaptive algorithms provide an efficient way to search large function spaces, and are increa...
Evolutionary algorithms (EAs) simulate the natural evolution of species by iteratively applying evol...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
Premature convergence is the main obstacle to the application of genetic algorithm. The study on co...
The current state-of-the-art of genetic algorithms is dominated by high-performing specialistsolvers...
3noIn this paper a method to increase the optimization ability of genetic algorithms (GAs) is propos...
Population diversity is essential for avoiding premature convergence in Genetic Algorithms (GAs) and...
. Genetic algorithms are widely used as optimization and adaptation tools, and they became important...
Evolutionary Algorithms is one of the fastest growing areas of computer science. The simple Genetic ...
Abstract. Over the last decade, variant of genetic algorithm (GA) approaches have been used to solve...
This paper surveys strategies applied to avoid premature convergence in Genetic Algorithms (GAs).Gen...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Premature convergence in the process of genetic algorithm (GA) for searching solution is frequently ...
Genetic Algorithms (GA) is an evolutionary inspired heuristic search algorithm. Like all heuristic s...
Abstract — Genetic algorithm (GA), as an important intelligence computing tool, is a wide research c...
Genetic adaptive algorithms provide an efficient way to search large function spaces, and are increa...
Evolutionary algorithms (EAs) simulate the natural evolution of species by iteratively applying evol...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
Premature convergence is the main obstacle to the application of genetic algorithm. The study on co...
The current state-of-the-art of genetic algorithms is dominated by high-performing specialistsolvers...
3noIn this paper a method to increase the optimization ability of genetic algorithms (GAs) is propos...
Population diversity is essential for avoiding premature convergence in Genetic Algorithms (GAs) and...
. Genetic algorithms are widely used as optimization and adaptation tools, and they became important...
Evolutionary Algorithms is one of the fastest growing areas of computer science. The simple Genetic ...