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 129 for “"Search algorithms"”.
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Efficient nearest-neighbor search algorithms for sub-Riemannian geometries
… been at the core of a significant amount of research in the past decades and it has recently gained traction outside academia with the rise of commercial interest in self-driving cars and autonomous aerial vehicles. Among the leading algorithms to tackle the problem are sampling-based planners, …
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New neighborhood search algorithms based on exponentially large neighborhoods
… problems is to employ heuristic (approximation) algorithms that can find nearly optimal solutions within a reasonable amount of computational time. An improvement algorithm is an approximation algorithm which starts with a feasible solution and iteratively attempts to obtain a better solution. …
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Assessing the Finite-Time Performance of Local Search Algorithms
… to assess a priori the effectiveness of local search algorithms, which makes the process of choosing parameters to improve their performance difficult. This dissertation introduces the B-acceptable solution probability in terms of B-acceptable solutions as a finite-time performance measure for …
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Validation and optimization of analog circuits using randomized search algorithms
… thesis, we introduce Duplex, a methodology for search and optimization. Duplex supports optimizing nonconvex nonlinear functions and functionals. We use duplex to solve problems in analog validation and machine learning. Duplex uses random tree data structures. Duplex is based on partitioning …
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Graph-based Vector Search Algorithms for Retrieval-Augmented AI Systems
… and leveraging approximate nearest neighbor search (ANNS) have thus become an important data processing primitive in AI systems following the introduction of retrievel-augmented generation (RAG). However, the complexity of tasks these AI systems aim to solve introduces challenges for existing …
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Computational experiments for local search algorithms for binary and mixed integer optimization
In this thesis, we implement and test two algorithms for binary optimization and mixed integer optimization, respectively. We fine tune the parameters of these two algorithms and achieve satisfactory performance. We also compare our algorithms with CPLEX on large amount of fairly large-size …
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Searching for Distant Galaxy Clusters : Optical Observations, Cluster Search Algorithms and the Cluster Selection Function
… redshift range 0.3 < z < 0.9. The power of the search method was demonstrated by a comparison with the cluster detections from the Voronoi tessellation. For the determination of the cluster selection function in HIROCS and COMBO-17 procedures to simulate galaxy clusters were introduced. Due to …
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Guidance and search algorithms for mobile robots: application and analysis within the context of urban search and rescue
Urban Search and Rescue is a dangerous task for rescue workers and for this reason the use of mobile robots to carry out the search of the environment is becoming common place. These robots are remotely operated and the search is carried out by the robot operator. This work proposes that common …
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Algorithms for combinatorial optimization in real-time and their automated refinements by genetics-based learning
The goal of this research is to develop a systematic, integrated method of designing efficient search algorithms that solve optimization problems in real time. Search algorithms studied in this thesis comprise meta-control and primitive search. The class of optimization problems addressed are …
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Cyclic exchange and related neighborhood structures for combinatorial optimization problems
In this thesis, we concentrate on neighborhood search algorithms based on very large-scale neighborhood structures. The thesis consists of three parts. In the first part, we develop a cyclic exchange neighborhood search based approach for partitioning problems. A partitioning problem is to divide a …
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Heuristic search under time and cost bounds
… Therefore it makes good sense that heuristic search is a foundational topic in artificial intelligence. In this context "search" refers to the process of finding a solution to the problem by considering a large, possibly infinite, set of potential plans of action. "Heuristic" refers to a rule …
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Automatic software generation and improvement through search based techniques
… task. Its automation is hence very valuable. Search algorithms have been successfully used to tackle many software engineering problems. Unfortunately, for some problems the traditional techniques have been of only limited scope, and search algorithms have not been used yet. We hence propose a …
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Probabilistic Trans-Algorithmic Search
… we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It …
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Improving Protein Docking Using Efficient Sustainable Evolutionary Algorithm
… in structure-based drug-design. Different search algorithms, such as Simulated Annealing, traditional Genetic Algorithm and Lamarckian Genetic Algorithm are used in AutoDock. However, the docking performance of these algorithms is still limited by the local optima issue in simulated …
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A Probabilistic Study of 3-SATISFIABILITY
… function value assigned to each solution. Local search algorithms provide useful tools for addressing a wide variety of intractable discrete optimization problems. Each such algorithm offers a distinct set of rules to intelligently exploit the solution space with the hope of finding an …
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Caracterización de los modelos de búsqueda de un agente con descripciones generalizadas de los nodos origen y destino
… satisfechas. ABSTRACT Single-agent search algorithms are, at first, a very useful technique for constructing intelligent systems. However, their study has been severely restricted to a few very well-defined domains and, in general terms, there is not a comprehensive description of …
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Combining search strategies for distributed constraint satisfaction.
… with other agents to solve the overall problem. Algorithms for solving DisCSPs can be classified as either systematic or local search with the former being complete and the latter incomplete. The algorithms generally assume that each agent has only one variable as they can solve DisCSP with CLPs …
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Hybrid algorithms for distributed constraint satisfaction.
… can be mainly classified into two families of algorithms: systematic search and local search. Systematic search algorithms are complete but may take exponential time. Local search algorithms often converge quicker to a solution for large problems but are incomplete. Problem solving could be …
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Simultaneous Generalized Hill Climbing Algorithms for Addressing Sets of Discrete Optimization Problems
Generalized hill climbing (GHC) algorithms provide a framework for using local search algorithms to address intractable discrete optimization problems. Many well-known local search algorithms can be formulated as GHC algorithms, including simulated annealing, threshold accepting, Monte Carlo …
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