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 331 for “"NP-hard"”.
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Learning NP-hard problems on networks using Geometric Deep Learning
… However, many problems on networks remain hard to define formally and even harder to solve exactly (for instance for computational constraints), requiring sub-optimal heuristics. In this work we show how Geometric Deep Learning, the generalization of Deep Learning to non-Euclidean domains …
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Linear and nonlinear semidefinite relaxations of some NP-hard problems
… bounds and obtain approximate solutions for NP-hard problems. This thesis introduces and studies several novel linear and nonlinear semidefinite relaxation models for some NP-hard problems. We first study the semidefinite relaxation of Quadratic Assignment Problem (QAP) based on matrix …
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An analysis of combinatorial search spaces for a class of NP-hard problems
… are state of the art for many classes of NP-hard combinatorial optimization problems such as maximum k-satisfiability, scheduling, and problems of graph theory. In this thesis we analyze combinatorial search spaces by expanding the objective function into a (sparse) series of basis …
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Exploiting structure to cope with NP-hard graph problems: Polynomial and exponential time exact algorithms
… finds it in polynomial time. When dealing with NP-hard problems, algorithms can only be expected to possess at most two out of these three desirable properties. All algorithms presented in this thesis are exact algorithms, which means that they always find an optimal solution. Demanding the …
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ON RELAY NODE PLACEMENT PROBLEM FOR SURVIVABLE WIRELESS SENSOR NETWORKS
… to overcome communication failures due to hardware failure, distributing sensors in an uneven geographic area, or unexpected obstacles between sensors. One common solution to overcome this problem is to place a minimum number of relay nodes among sensors so that the communication among …
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Scalable second-order Riemannian optimization for K-means clustering
… formulation for clustering is a worst-case NP-hard discrete optimization problem. Despite being NP-hard, the SDP relaxation of the discrete formulation is guaranteed to recover the true cluster whenever it is statistically solvable. In this thesis, we propose to solve the relaxed K-means …
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Maximum Clique in Geometric Intersection Graphs
… labelling. This method is used to show the NP- hardness of finding a maximum clique in various geometric intersection graphs, acting as a way to augment the commonly used co-2-subdivision approach. Finally, finding maximum clique in two classes of geometric intersection graphs are proven to …
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Reconfiguration of Fault-Tolerant VLSI Systems
… other related architectures reconfiguration is NP-hard. For those reconfiguration problems that can be solved in polynomial time, we present fast (and in many cases asymptotically optimal) algorithms. For the NP-hard reconfiguration problems, we propose several strategies. For some problems, …
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On the computational complexity of portal and push-pull block puzzles
… Portal, a popular video game, is shown to be NP-hard or PSPACE-complete depending on the game mechanics allowed. Push-pull block puzzles are games, similar to Sokoban, which involve moving a 'robot' on a square grid with obstacles and blocks that can be pushed or pulled by the robot into …
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Polynomial time optimal algorithm for stencil row planning in e-beam lithography
… planning problem has been proven to be an NP-hard problem. As its most essential step, the 1D row ordering is believed hard as well, and no polynomial time optimal solution has been provided so far. Previous research formulates the problem as the travelling salesman problem, which is …
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Pattern extraction and clustering for high-dimensional discrete data
… factorization. These combinatorial problems are NP-hard. Our goal is to develop effective approximation algorithms with good theoretical properties and apply them to solve various real application problems. We reformulate each of the problems as a special clustering problem that has the same …
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On Training Neurons with Bounded Compilations
… an Ordered Binary Decision Diagram (OBDD), is an NP-hard problem. In this thesis, we consider the problem of training a neuron from data, subject to the constraint that it has a compact representation as an OBDD. Our approach is based on the observation that a neuron can be compiled into an OBDD …
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Connections between circuit analysis problems and circuit lower bounds
… analysis problem takes a Boolean function f as input (where f is represented either as a logical circuit, or as a truth table) and determines some interesting property of f. Examples of circuit analysis problems include Circuit Satisfiability, Circuit Composition, and the Minimum Size Circuit …
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Diverse sampling of streaming data
… optimal solution to the dispersion problem is NP-hard. Therefore, existing and proposed solutions are approximation algorithms. This work evaluates the performance of dierent algorithms in practice and compares them to the theoretical guarantees.
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A Hybrid multi-agent architecture and heuristics generation for solving meeting scheduling problem
… the followings categories: (i) P problems, (ii) NP problems, (iii) NP-complete problems, and (iv) NP-hard problems. A method for computing the solution to NP-hard problems, using the algorithms and computational power available nowadays in reasonable time frame remains undiscovered. And …
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QoS and security-aware task assignment and scheduling in real-time systems
… as MILP, and then its complexity is proved to be NP-hard. An online efficient heuristic algorithm is developed as the problem is NP-hard. Simulation studies for a wide range of workload scenarios showed that the proposed algorithm outperforms a set of baseline algorithms. Further, the proposed …
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Robust Nonlinear Control Using Bilinear Matrix Inequalities With Application to a Batch Crystallization Process
… optimization problem, has been shown to be NP-hard, and its efficient solution is also an open research problem. Various solution strategies have been incorporated to a branch and bound algorithm solving the aforementioned optimization problem, and were compared for various controller …
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Load volume considerations in the collision free route planning of material handling devices in FMS
… AGVs to avoid collision is known to be an NP-Hard problem. In this research, we address the problem of optimal and efficient routing of AGVs through a guide path network.
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Survivable paths in multilayer networks
… finding the minimum survivable path set is NP-hard, whereas both of the restricted versions of the problem can be solved in polynomial time. We formulate the problem as Integer Linear Programs (ILPs), and use these formulations to develop heuristics and approximation algorithms. Next, we …
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Two Combinatorial Optimization Problems at the Interface of Computer Science and Operations Research
… discrete optimization problem is proven to be NP-hard. To solve this problem, exact algorithms and heuristic methods are presented. Different multi-objective problems with various numbers of objectives and constraints are used to compare the performances of the proposed algorithms and …
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