This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic operators. After the literature overview we used a three-dimensional genetic algorithm to solve a combinatorial task called Kirkman’s Schoolgirl Problem. The first results were not good, but we improved convergence of an algorithm by adding more genetic operators. We also used problem dependent mutation, where we tried to repair the incorrect solution by using the simple heuristic method. Finally, we got a solid number of correct solutions, but we know there is enough room for other improvements
This thesis presents description of Genetic algorithm. The description begins with theory of complex...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...
This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic ...
This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic ...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
For the solution of combinatorial problem, various algorithms has been investigated. However, almost...
Genetic Algorithms use life as their model to solve difficult problems in computer science. They use...
Introduction. Practical tasks (location of service points, creation of microcircuits, scheduling, et...
In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applicatio...
In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applicatio...
An important class of combinatorial optimization problems are the Multidimensional 0/1 Knapsacks, an...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approa...
The k-means problem is one of the most popular models of cluster analysis. The problem is NP-hard, a...
This thesis presents description of Genetic algorithm. The description begins with theory of complex...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...
This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic ...
This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic ...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
For the solution of combinatorial problem, various algorithms has been investigated. However, almost...
Genetic Algorithms use life as their model to solve difficult problems in computer science. They use...
Introduction. Practical tasks (location of service points, creation of microcircuits, scheduling, et...
In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applicatio...
In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applicatio...
An important class of combinatorial optimization problems are the Multidimensional 0/1 Knapsacks, an...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approa...
The k-means problem is one of the most popular models of cluster analysis. The problem is NP-hard, a...
This thesis presents description of Genetic algorithm. The description begins with theory of complex...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...
The Traveling Salesman Problem (TSP) is one of the extensively studied combinatorial optimization pr...