Routing optimization refers to finding the most efficient path for data to travel between two devices on a network. In this paper, we propose the use of the Quantum Approximate optimization Algorithm (QAOA) as a novel...
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ISBN:
(纸本)9783903176621;9798350351132
Routing optimization refers to finding the most efficient path for data to travel between two devices on a network. In this paper, we propose the use of the Quantum Approximate optimization Algorithm (QAOA) as a novel approach to routing optimization in the context of 6G networks. To this end, we first develop a cost function for single source single destination routing, which is then converted into a Quadratic Unconstrained Binary optimization formulation. We subsequently extract the equivalent Variational Quantum Circuit of the QAOA from the optimization formulation. To test the performance of the QAOA, we utilize IBM's Qiskit toolkit and QASM-simulator and the Constrained by Linear Approximation optimizer to update the circuit parameters. simulation results show that the proposed approach converges to the optimal solution, and only after less than 25 iteration, the QAOA was able to find the optimal path for the routing problem.
This paper presents a Bayesian optimization framework for the automatic tuning of shared controllers which are defined as a Model Predictive Control (MPC) problem. The proposed framework includes the design of perform...
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ISBN:
(纸本)9798350384581;9798350384574
This paper presents a Bayesian optimization framework for the automatic tuning of shared controllers which are defined as a Model Predictive Control (MPC) problem. The proposed framework includes the design of performance metrics as well as the representation of user inputs for simulation-based optimization. The framework is applied to the optimization of a shared controller for an Image Guided Therapy robot. VR-based user experiments confirm the increase in performance of the automatically tuned MPC shared controller with respect to a hand-tuned baseline version as well as its generalization ability.
The proceedings contain 33 papers. The topics discussed include: driving energy efficiency at scale by mass deployment of ai-based chiller energy optimization: exploring a scalable framework for ai-driven chiller ener...
ISBN:
(纸本)9798400709302
The proceedings contain 33 papers. The topics discussed include: driving energy efficiency at scale by mass deployment of ai-based chiller energy optimization: exploring a scalable framework for ai-driven chiller energy optimization: a case study on mass deployment in Hong Kong;AI-powered earth disaster management: a collaborative innovation platform;enhancing travel planning and experiences with multimodal ChatGPT 4.0;systems engineering enhanced by AI-driven multiphysics simulation: multiphysics modeling and simulation with artificial intelligence / multiphysics modeling and simulation for technology transfer using artificial intelligence;the knowledge training system based on machine learning technology;and leveraging automated POS tagging to decode parent-infant interactions in digital gameplays.
Optimizing the key parameters of the range extender has an important impact on improving the fuel economy and reducing the emissions of the range extender electric vehicle. Firstly, GT-Power is used to establish a one...
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The article introduces the stochastic N-k interdiction problem for power grid operations and planning that aims to identify a subset of k components (out of N components) that maximizes the expected damage measured in...
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ISBN:
(纸本)9798350372793;9798350372786
The article introduces the stochastic N-k interdiction problem for power grid operations and planning that aims to identify a subset of k components (out of N components) that maximizes the expected damage measured in terms of load shed. Uncertainty is modeled through a fixed set of outage scenarios, where each scenario represents a subset of components removed from the grid. We formulate the stochastic N-k interdiction problem as a bi-level optimization problem and propose two algorithmic solutions. The first approach reformulates the bi-level stochastic optimization problem to a single-level, mixed-integer linear program (MILP) by dualizing the inner problem and solving the resulting problem directly using a MILP solver to global optimality. The second is a heuristic cutting-plane approach, which is exact under certain assumptions. We compare these approaches in terms of computation time and solution quality using the IEEE-Reliability Test System and present avenues for future research.
The optimization of 4D trajectory and its benefits for continuous descent operation(CDO) are the prerequisite for advanced arrival traffic automation and environmental management. Firstly, It was established that mult...
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ISBN:
(纸本)9798400709760
The optimization of 4D trajectory and its benefits for continuous descent operation(CDO) are the prerequisite for advanced arrival traffic automation and environmental management. Firstly, It was established that multi-phase optimal control model for vertical profiles with the objectives of minimizing time and fuel consumption, respectively. Then, a trajectory optimization results for a CDO is given based on the pseudo spectral method. Finally, 4D trajectory optimization and benefit comparison experiments in continuous descent operation mode are conducted using actual trajectory data. The experimental results show that ideal 4D trajectories for CDO could be achieved. With the minimum time as the optimization objective, the average operation time and CO2 emission were reduced by 41% and 25% respectively. With the minimum fuel consumption as the optimization objective, the operation time and CO2 emission decreases by 33% and 32%, respectively.
This study analyzes and optimizes the key structural components of a handling manipulator based on fatigue simulation and finite element simulation methods. Taking the handling manipulator as the research object, the ...
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Efficient Global optimization (EGO) is a very important black-box optimization framework for solving expensive optimization problems, which appear in high-fidelity simulation-based optimization. EGO operates by employ...
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The proceedings contain 12 papers. The special focus in this conference is on Numerical Analysis and optimization: Theory, Methods, Applications and Technology Transfer. The topics include: Largest Small n-polygons: N...
ISBN:
(纸本)9783030720391
The proceedings contain 12 papers. The special focus in this conference is on Numerical Analysis and optimization: Theory, Methods, Applications and Technology Transfer. The topics include: Largest Small n-polygons: Numerical Optimum Estimates for n ≥ 6;computational Science in the 17th Century. Numerical Solution of Algebraic Equations: Digit–by–Digit Computation;Behavior of Limited Memory BFGS When applied to Nonsmooth Functions and Their Nesterov Smoothings;subgradient Smoothing Method for Nonsmooth Nonconvex optimization;on Some optimization Problems that Can Be Solved in O(n) Time;Iteration Complexity of a Fixed-Stepsize SQP Method for Nonconvex optimization with Convex Constraints;modelling and Inferring the Triggering Function in a Self-Exciting Point Process;a New Multi-point Stepsize Gradient Method for optimization;A Julia Implementation of Algorithm NCL for Constrained optimization;a Survey on modeling Approaches for Generation and Transmission Expansion Planning Analysis.
Recent applications like mmWave technologies require antenna characteristics such as high gain and wide bandwidth for smooth operation with high speed. Hence, this paper presents a novel pi-shaped patch antenna framed...
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Recent applications like mmWave technologies require antenna characteristics such as high gain and wide bandwidth for smooth operation with high speed. Hence, this paper presents a novel pi-shaped patch antenna framed within a square structure for mmWave applications at 28 GHz. In the process of designing a four-element linear-planar antenna array (LPAA), a thin single antenna element is designed on a 0.275 mm Rogers 5880 substrate with a dielectric constant of 2.2. The proposed single-element antenna provides a gain of 3 dBi at 28 GHz and a wide impedance bandwidth ranging from 22.482 GHz to 40.511 GHz. Then, this proposed structure is transformed into a four-element LPAA with a compact dimension of 0.263 mm x 18.55 mm x 23.99 mm. To enhance and predict the impedance bandwidth of the proposed LPAA, mathematical modeling using response surface methodology and constrained numerical optimization is applied. In the optimization process of the antenna, independent factors such as substrate height (Hs) and interelement spacing (d) that influence the antenna's responses such as impedance bandwidth (BW) and operating frequency (Fr) are considered. These factors are varied repeatedly and simulated using computer simulation technology (CST) suite 2019 for preparing the dataset, which is used as an input for mathematical modeling. Then, response surface methodology (RSM) is employed to relate the responses with independent factors. Models are validated using analysis of variance (ANOVA). The optimum parameters determined by applying constrained numerical optimization are substrate height (Hs) and interelement spacing (d) of values 0.263 mm and 5.61 mm, respectively. The optimized LPAA provides a wide bandwidth of 11 GHz and a peak gain of 9.25 dBi. The antenna also gives radiation efficiency of >= 98.5% and VSWR of less than 2 in its operating frequency range. The results included here are simulated using the CST EM solver and validated using the Ansys High-Frequency Simulati
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