Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 40 for “"Ant Colony Optimization"”.
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Ant colony optimization for agile motion planning
… This thesis investigates the suitability of the Ant Colony Optimization (ACO) heuristic for the agile vehicle motion planning problem. An ACO implementation tailored to the motion planning problem was designed and tested against an existing genetic algorithm solution method for validation. …
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Using ant colony optimization for routing in microprocesors
Power consumption is an important constraint on VLSI systems. With the advancement in technology, it is now possible to pack a large range of functionalities into VLSI devices. Hence it is important to find out ways to utilize these functionalities with optimized power consumption. This work …
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A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing
… 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 …
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A hierarchical approach to improve the ant colony optimization algorithm
<p>The ant colony optimization algorithm (ACO) is a fast heuristic-based method for finding favorable solutions to the traveling salesman problem (TSP). When the data set reaches larger values however, the ACO runtime increases dramatically. As a result, clustering nodes into groups is an effective …
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Improving peer review with ACORN : Ant Colony Optimization algorithm for Reviewer's Network
… a new system for conference peer review based on ant colony optimization (ACO) algorithms. In our model, each reviewer has a set of ants that goes out and finds articles. The reviewer assesses the paper that the ant brings according to the criteria specified by the conference organizers and the …
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Reconfiguration of distribution systems to reduce power loss using ant Colony Optimization and Simulated Annealing
… distribution grids and running power flows. The optimization is executed with two techniques: Simulated annealing (SA) and ant colony optimization (ACO). SA is a well know and widely used optimization technique for reconfiguration problems. It is an implementation based on keeping radiality and …
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An Investigation Into a Hybrid Genetic Programming and Ant Colony Optimization Method for Credit Scoring
… technique based on Genetic Programming (GP) and Ant Colony Optimization (ACO) techniques for inducing data classification rules. The proposed hybrid approach aims to improve on the accuracy of data classification rules produced by the original GP technique, which uses randomly generated initial …
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Extending the Utility of Ant Colony Optimization Through the Incorporation of an Intraclass Correlation Coefficient to Assess for Rater Consistency
<p>Ant Colony Optimization (ACO) is a flexible algorithm designed to solve complex combinatorial problems. While the method was derived from the behavior of ants by researchers in the field of computer science, its application to solving complex combinatorial problems is widespread in a growing …
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Ant colony heuristics for the dynamic facility layout problem
… research proposes three heuristics based on the ant colony optimization (ACO) heuristic to solve the DFLP. The performance of the heuristics was evaluated using two data sets taken from the literature. Results obtained show that the proposed heuristics are effective for the dynamic facility …
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Bi objective multi depot location routing problem with time window for EVs
… combining a hybrid Genetic Algorithm (GA) and Ant Colony Optimization (ACO), was developed to optimize depot locations and EV routes, minimizing operational costs and balancing driver workloads. The approach accounts for depot and vehicle capacities, vehicle mileage limits, and EV charging …
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SNAP Biclustering
This thesis presents a new ant-optimized biclustering technique known as SNAP biclustering, which runs faster and produces results of superior quality to previous techniques. Biclustering techniques have been designed to compensate for the weaknesses of classical clustering algorithms by allowing …
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A proposal for an improved version of EigenAnt algorithm with performance evaluation on combinatorial optimization problems
The EigenAnt algorithm has recently been introduced to solve the problem of finding the shortest path between two nodes by using dynamics involving local pheromone evaporation. This algorithm has a mathematical proof of convergence to the shortest path between two nodes. In this thesis, the …
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High Quality Test Generation at the Register Transfer Level
… in circuit size has also lead to significant growth in testing effort required to verify the design. In order to cope with the required effort, the testing problem must be approached from several different design levels. In particular, exploiting the Register Transfer Level for test …
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Increasing Branch Coverage with Dual Metric RTL Test Generation
… Verilator, which also automatically creates mutants and the corresponding mutated C++ design, based on arithmetic, logical and relational operators during conversion. With the help of extracted Data Dependency and Control Flow Graphs, in every <golden, mutation> pair, branches containing …
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Improving Bio-Inspired Frameworks
… BEACON, in terms of performance. BEACON is an Ant Colony Optimization (ACO) based test generation framework. Similar to other ACO frameworks, BEACON also has a good scope in improving performance using parallel computing. We try to exploit the available parallelism using both multi-core Central …
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Problem dependent metaheuristic performance in Bayesian network structure learning.
… has considered BN structure learning as an optimization problem. However, the finding of optimal BN from data is NP-hard. This fact has driven the use of heuristic algorithms for solving this kind of problem. Amajor recent focus in BN structure learning is on search and score algorithms. In …
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Reduced-complexity near-optimal Ant-Colony-aided multi-user detection for CDMA systems
Reduced-complexity near-maximum-likelihood Ant-Colony Optimization (ACO) assisted Multi-User Detectors (MUDs) are proposed and investigated. The exhaustive search complexity of the optimal detection algorithm may be deemed excessive for practical applications. For example, a Space-Time Block Coded …
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Pruning methods for rule induction
… propose a new instance reduction method based on Ant Colony Optimization (ACO). We evaluate the effectiveness of this instance reduction method for k nearest neighbour algorithms in term of predictive accuracy and amount of reduction. Then we compared it with other instance reduction methods.We …
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Development of Construction Projects Scheduling with Evolutionary Algorithms
… such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) in construction engineering and management domains remain poorly understood. Furthermore, hybrid algorithms such as Hybrid Genetic Algorithm-Particle Swarm Optimization (HGAPSO) and Shuffled Frog …
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