Visando contribuir com o estado-da-arte de sistemas bioinspirados em formigas na robóotica, neste trabalho é abordado o problema do controle de um grupo de robôs para a solução coletiva das tarefas de exploração do ambiente e localização de objetos. Para isso, são utilizados algoritmos inspirados em colônias de formigas. O objetivo deste trabalho, portanto, é o desenvolvimento de um sistema de controle de navegação baseado em colônia de formigas para um time de robôs, de maneira que os robôs resolvam esses problemas utilizando estratégias de controle individuais e simples. Esse sistema tem como base a utilização de marcadores ou feromônios artificiais, que podem ser depositados pelos robôs para marcar determinadas posiçôes do ambiente / Aiming to advance the state-of-the-art of ant bioinspired systems in robotic applications, in this work we study the problem of controling a group of robots for solving colective tasks on environment exploration and object localization. To this end, we used algorithms inspired in ant colonies. Therefore, the objective of this work is to develop a navigation control system based on ant colony can solve the problems using simple control strategies. This system uses marks or artificial pheromones that can be released by the robots to mark specific positions in the environment

Visando contribuir com o estado-da-arte de sistemas bioinspirados em formigas na robóotica, neste trabalho é abordado o problema do controle de um grupo de robôs para a solução coletiva das tarefas de exploração do ambiente e localização de objetos. Para isso, são utilizados algoritmos inspirados em colônias de formigas. O objetivo deste trabalho, portanto, é o desenvolvimento de um sistema de controle de navegação baseado em colônia de formigas para um time de robôs, de maneira que os robôs resolvam esses problemas utilizando estratégias de controle individuais e simples. Esse sistema tem como base a utilização de marcadores ou feromônios artificiais, que podem ser depositados pelos robôs para marcar determinadas posiçôes do ambiente / Aiming to advance the state-of-the-art of ant bioinspired systems in robotic applications, in this work we study the problem of controling a group of robots for solving colective tasks on environment exploration and object localization. To this end, we used algorithms inspired in ant colonies. Therefore, the objective of this work is to develop a navigation control system based on ant colony can solve the problems using simple control strategies. This system uses marks or artificial pheromones that can be released by the robots to mark specific positions in the environment

Multistage Interconnection Networks (MIN) are popular in switching and communication applications. It has been used in telecommunication and parallel computing systems for many years. The new challenge facing optical MIN is crosstalk, which is caused by coupling two signals within a switching element. Crosstalk is not too big an issue in the Electrical Domain, but due to the stringent Bit Error Rate (BER) constraint, it is a big major concern in the Optical Domain. In this research dissertation, we will study the blocking probability in the optical network and we will study the deterministic conditions for strictly non-blocking Vertical Stacked Optical Benes Networks (VSOBN) with and without worst-case scenarios. We will establish the upper bound on blocking probability of Vertical Stacked Optical Benes Networks with respect to the number of planes used when the non-blocking requirement is not met. We will then study routing in WDM Benes networks and propose a new routing algorithm so that the number of wavelengths can be reduced. Since routing in WDM optical network is an NP-hard problem, many heuristic algorithms are designed by many researchers to perform this routing. We will also develop a genetic algorithm, simulated annealing algorithm and ant colony technique and apply these AI algorithms to route the connections in WDM Benes network.

This diploma thesis deals with Ant Colony algorithms and their usage for solving Travelling Salesman Problems and Vehicle Routing Problems. These algorithms are metaheuristics offering new approach to solving NP-hard problems. Work begins with a description of the forementioned tasks including ways to tackle them. Next chapter analyses Ant Colony metaheuristic and its possible usage and variations. The most important part of the thesis is practical and is represented by application Ant Colony Optimization Framework. It is easily extensible application written in Java that is able to solve introduced problems. In conclusion this work presents analysis of solutions on test data.

This thesis focuses on applying one of the rapidly growing non-deterministic optimization algorithms, the ant colony algorithm, for simulating automatic hose/pipe routing with several conflicting objectives. Within the thesis, methods have been developed and applied to single objective hose routing, multi-objective hose routing and multi-hose routing. The use of simulation and optimization in engineering design has been widely applied in all fields of engineering as the computational capabilities of computers has increased and improved. As a result of this, the application of non-deterministic optimization techniques such as genetic algorithms, simulated annealing algorithms, ant colony algorithms, etc. has increased dramatically resulting in vast improvements in the design process. Initially, two versions of ant colony algorithms have been developed based on, respectively, a random network and a grid network for a single objective (minimizing the length of the hoses) and avoiding obstacles in the CAD model. While applying ant colony algorithms for the simulation of hose routing, two modifications have been proposed for reducing the size of the search space and avoiding the stagnation problem. Hose routing problems often consist of several conflicting or trade-off objectives. In classical approaches, in many cases, multiple objectives are aggregated into one single objective function and optimization is then treated as a single-objective optimization problem. In this thesis two versions of ant colony algorithms are presented for multihose routing with two conflicting objectives: minimizing the total length of the hoses and maximizing the total shared length (bundle length). In this case the two objectives are aggregated into a single objective. The current state-of-the-art approach for handling multi-objective design problems is to employ the concept of Pareto optimality. Within this thesis a new Pareto-based general purpose ant colony algorithm (PSACO) is proposed and applied to a multi-objective hose routing problem that consists of the following objectives: total length of the hoses between the start and the end locations, number of bends, and angles of bends. The proposed method is capable of handling any number of objectives and uses a single pheromone matrix for all the objectives. The domination concept is used for updating the pheromone matrix. Among the currently available multi-objective ant colony optimization (MOACO) algorithms, P-ACO generates very good solutions in the central part of the Pareto front and hence the proposed algorithm is compared with P-ACO. A new term is added to the random proportional rule of both of the algorithms (PSACO and P-ACO) to attract ants towards edges that make angles close to the pre-specified angles of bends. A refinement algorithm is also suggested for searching an acceptable solution after the completion of searching the entire search space. For all of the simulations, the STL format (tessellated format) for the obstacles is used in the algorithm instead of the original shapes of the obstacles. This STL format is passed to the C++ library RAPID for collision detection. As a result of using this format, the algorithms can handle freeform obstacles and the algorithms are not restricted to a particular software package.