Browsing by Subject "Ant Colony Optimization"
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Item A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing(2012-07-16) McDonald, WalterAn algorithm is presented that is capable of producing Pareto-optimal solutions for multi-objective infrastructure routing problems: the Multi-Objective Ant Colony Optimization (MOACO). This algorithm offers a constructive search technique to develop solutions to different types of infrastructure routing problems on an open grid framework. The algorithm proposes unique functions such as graph pruning and path straightening to enhance both speed and performance. It also possesses features to solve issues unique to infrastructure routing not found in existing MOACO algorithms, such as problems with multiple end points or multiple possible start points. A literature review covering existing MOACO algorithms and the Ant Colony algorithms they are derived from is presented. Two case studies are developed to demonstrate the performance of the algorithm under different infrastructure routing scenarios. In the first case study the algorithm is implemented into the Ice Road Planning module within the North Slope Decision Support System (NSDSS). Using this ice road planning module a case study is developed of the White Hills Ice road to test the performance of the algorithm versus an as-built road. In the second case study, the algorithm is applied to a raw water transmission routing problem in the Region C planning zone of Texas. For both case studies the algorithm produces a set of results which are similar to the preliminary designs. By successfully applying the algorithm to two separate case studies the suitability of the algorithm to different types of infrastructure routing problems is demonstrated.Item Multi-input multi-output (MIMO) detection by a colony of ants(2009-06-02) Jaber, Dana N.The traditional mobile radio channel has always suffered from the detrimental effects of multipath fading. The use of multiple antennae at both ends of the wireless channel has proven to be very effective in combatting fading and enhancing the channel's spectral efficiency. To exploit the benefits offered by Multi-Input Multi-Output (MIMO) systems, both the transmitter and the receiver have to be optimally designed. In this thesis, we are concerned with the problem of receiver design for MIMO systems in a spatial multiplexing scheme. The MIMO detection problem is an NP-hard combinatorial optimization problem. Solving this problem to optimality requires an exponential search over the space of all possible transmitted symbols in order to find the closest point in a Euclidean sense to the received symbols; a procedure that is infeasible for large systems. We introduce a new heuristic algorithm for the detection of a MIMO wireless system based on the Ant Colony Optimization (ACO) metaheuristic. The new algorithm, AntMIMO, has a simple architecture and achieves near maximum likelihood performance in polynomial time.