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Novel Applications of Ant Algorithms
Korgo, Jakub ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
Ant algorithms have been used for a variety of combinatorial optimization problems. One of these problems, where ant algorithms haven't been used, is the design of transition rules for cellular automata (CA). Which is a problem that this master's thesis is focused on. This work begins with an introduction into ant algorithms and a overview of its applications, followed by an introduction into CA. In the next part the author proposes a way how to encode rules of CA into a graph which is used in ant algorithms. The last part of this thesis contains an application of encoded graph on elitist ant system and MAX-MIN ant system. This is followed by experimental results of creating transition rules for CA problems by these algorithms.
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Experiments with the Swarm Intelligence
Hula, Tomáš ; Zbořil, František (referee) ; Grulich, Lukáš (advisor)
This work deals with the issue of swarm intelligence as a subdiscipline of artificial intelligence. It describes biological background of the dilemma briefly and presents the principles of searching paths in ant colonies as well. There is also adduced combinatorial optimization and two selected tasks are defined in detail: Travelling Salesman Problem and Quadratic Assignment Problem. The main part of this work consists of description of swarm intelligence methods for solving mentioned problems and evaluation of experiments that were made on these methods. There were tested Ant System, Ant Colony System, Hybrid Ant System and Max-Min Ant System algorithm. Within the work there were also designed and tested my own method Genetic Ant System which enriches the basic Ant System i.a. with development of unit parameters based on genetical principles. The results of described methods were compared together with the ones of classical artificial intelligence within the frame of both solved problems.
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Ant Colony Optimization for Solving Big Instances of TSP
Ramosová, Patrícia ; Jaroš, Jiří (referee) ; Bidlo, Michal (advisor)
Currently, many applications place emphasis on finding the optimal solution to a particular problem. However, it is typical for some tasks that their complexity increases exponentially depending on the size of the instance. A typical example of such a problem is the Traveling Salesman Problem (TSP). One class of methods that have proven to be very helpful in solving TSPs are ant algorithms. Nonetheless, they reached their limit - a high number of cities in the instance and became almost unusable due to time and memory requirements. This bachelor thesis aims to modify the ant algorithm and create a system capable of quickly and efficiently solve large-scale TSPs without significant loss in the quality of the solution found. Optimization will focus on reducing memory complexity and total execution time.
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Ant Colony Optimization for Solving Big Instances of TSP
Ramosová, Patrícia ; Jaroš, Jiří (referee) ; Bidlo, Michal (advisor)
Currently, many applications place emphasis on finding the optimal solution to a particular problem. However, it is typical for some tasks that their complexity increases exponentially depending on the size of the instance. A typical example of such a problem is the Traveling Salesman Problem (TSP). One class of methods that have proven to be very helpful in solving TSPs are ant algorithms. Nonetheless, they reached their limit - a high number of cities in the instance and became almost unusable due to time and memory requirements. This bachelor thesis aims to modify the ant algorithm and create a system capable of quickly and efficiently solve large-scale TSPs without significant loss in the quality of the solution found. Optimization will focus on reducing memory complexity and total execution time.
|
|
|
Novel Applications of Ant Algorithms
Korgo, Jakub ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
Ant algorithms have been used for a variety of combinatorial optimization problems. One of these problems, where ant algorithms haven't been used, is the design of transition rules for cellular automata (CA). Which is a problem that this master's thesis is focused on. This work begins with an introduction into ant algorithms and a overview of its applications, followed by an introduction into CA. In the next part the author proposes a way how to encode rules of CA into a graph which is used in ant algorithms. The last part of this thesis contains an application of encoded graph on elitist ant system and MAX-MIN ant system. This is followed by experimental results of creating transition rules for CA problems by these algorithms.
|
|
|
Experiments with the Swarm Intelligence
Hula, Tomáš ; Zbořil, František (referee) ; Grulich, Lukáš (advisor)
This work deals with the issue of swarm intelligence as a subdiscipline of artificial intelligence. It describes biological background of the dilemma briefly and presents the principles of searching paths in ant colonies as well. There is also adduced combinatorial optimization and two selected tasks are defined in detail: Travelling Salesman Problem and Quadratic Assignment Problem. The main part of this work consists of description of swarm intelligence methods for solving mentioned problems and evaluation of experiments that were made on these methods. There were tested Ant System, Ant Colony System, Hybrid Ant System and Max-Min Ant System algorithm. Within the work there were also designed and tested my own method Genetic Ant System which enriches the basic Ant System i.a. with development of unit parameters based on genetical principles. The results of described methods were compared together with the ones of classical artificial intelligence within the frame of both solved problems.
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