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 13 of 13 for “"Binary optimization"”.
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Improving binary optimization algorithms using genuine uniform initialization
… play a crucial role in solving complex optimization problems. The effectiveness of these algorithms is significantly influenced by the initial population of candidate solutions. This thesis investigates the critical aspect of initialization in population-based metaheuristic algorithms. …
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Computational experiments for local search algorithms for binary and mixed integer optimization
… 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 instances. …
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New frontiers in population-based multi-objective feature selection
… We frame feature selection as a multi-objective binary optimization task with the objectives of enhancing accuracy and reducing the feature count. Given that feature selection, along with binary optimization problems in general, is a NP-hard problem since the size of search space increases …
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Combinatorial optimization using quantum computing
… explores quantum computing for combinatorial optimization through the Traveling Salesman Problem (TSP), which aims to find a minimum-cost Hamiltonian cycle visiting each city exactly once. Using Qiskit, we implement the Quantum Approximate Optimization Algorithm (QAOA) on both simulators and …
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Quantum-Powered Battery Scheduling in Modern Distribution Grids
… (CQM) on D-Wave’s hybrid solver as well as a binary quadratic model (BQM), this thesis solves the optimal battery scheduling problem for a large number of batteries. To formulate the BQM, a quadratic unconstrained binary optimization (QUBO) format was chosen and in order to fine-tune the QUBO …
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Machine Learning and Quantum Computing for Optimization Problems in Power Systems
While optimization problems are ubiquitous in all domains of engineering, they are of critical importance to power systems engineers. A safe and economical operation of the power systems entails solving many optimization problems such as security-constrained unit commitment, economic dispatch, …
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Quantum computing for biophysical and optimization problems
… incorporates a QUBO (Quadratic Unconstrained Binary Optimization) encoding of the design problem that is amenable to adiabatic quantum platforms such as the D-Wave device. For the polymer sampling problem — where the objective is to sample both the sequence and the conformation of polymers …
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Graphical Methods for Image Compositing and Completion
… a few drawbacks in the literature. It adopts a binary optimization technique to construct an image summary, which is then shifted according to a map, calculated with combinatorial optimization, to complete the image. I also present the formulation with which the proposed method can be extended …
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Optimizing Quantum Annealing for Trapped Ions: Performance, Resources, and Noise Mitigation
… is a promising method for solving combinatorial optimization problems with quantum computers, but its practical performance on near-term devices is constrained by the architecture of the underlying platform, the presence of noise, and the design of the annealing protocol itself. This thesis …
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Optimizing Runtime Performance of Dynamically Typed Code
… involves fewer opportunities for compiler optimizations, and no detection of type errors at compile time. In order to provide the benefits of static and dynamic typing, hybrid typing languages provide both typing approaches in the very same programming language. Nevertheless, dynamically …
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Guided Automatic Binary Parallelisation
… legacy binaries. The first, GBR (Guided Binary Recompilation), is a tool that recompiles stripped application binaries without the need for the source code or relocation information. GBR performs static binary analysis to determine how recompilation should be undertaken, and produces a …
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Programmable stochastic processors
… It demonstrates the benefit of using compiler optimizations that optimize a binary to enable more energy savings when operating at a non-zero error rate. It also demonstrates significant benefits for a programmable stochastic processor prototype that improves energy efficiency by carefully …
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Engineering quantum computing technologies: from compact modelling to applications
L'abstract è presente nell'allegato / the abstract is in the attachment