#optimization
13 resultsMinimization of Frequency Deviations in Power Network by using majorant functions
Oleg O. Khamisov
The paper derives conservative bounds on how much power‑system frequencies can deviate after disturbances and proposes a zero‑order optimization method to tune control parameters,…
Optimal charging guidance strategies for electric vehicles by considering dynamic charging requests in a time-varying road network
Yongxing Wang, Jun Bi
The paper proposes two optimal charging guidance strategies for electric vehicles that account for dynamic charging requests and a time‑varying road network, one minimizing travel…
Transactive Energy System: Market-Based Coordination of Distributed Energy Resources
Sen Li, Jianming Lian, Antonio Conejo +1
The paper proposes a unified framework to compare and analyze market‑based (transactive) coordination strategies for distributed energy resources, outlining key components such as…
Optimizing quantum heuristics with meta-learning
Max Wilson, Sam Stromswold, Filip Wudarski +3
The paper investigates using meta‑learning techniques to optimize variational quantum algorithms, showing that meta‑learners can more reliably find near‑optimal parameters and are…
Speculative Execution for Guided Visual Analytics
Fabian Sperrle, Jürgen Bernard, Michael Sedlmair +2
The paper introduces Speculative Execution for Visual Analytics, a technique that automatically generates and visualizes alternative model configurations without changing the curre…
Energy Efficiency Optimization for UAV-assisted Backscatter Communications
Shengzhi Yang, Yansha Deng, Xuanxuan Tang +2
The paper proposes a UAV‑assisted backscatter communication system for IoT devices and optimizes the UAV’s data‑collection location to maximize energy efficiency while meeting outa…
A Convex-Combinatorial Model for Planar Caging
Bernardo Aceituno-Cabezas, Hongkai Dai, Alberto Rodriguez
The paper introduces a convex-combinatorial optimization model to represent planar caging, allowing robots to enclose an object's configuration with finger obstacles for robust man…
An Adaptive Pole-Matching Method for Interpolating Reduced-Order Models
Yao Yue, Lihong Feng, Peter Benner
The paper introduces an adaptive method for building parametric reduced-order models by matching and interpolating the poles of reduced models, using a branch‑and‑bound optimizatio…
EVO* 2019 -- Late-Breaking Abstracts Volume
A. M. Mora, A. I. Esparcia-Alcázar
This volume compiles the late‑breaking abstracts presented at the EVO* 2019 conference, showcasing ongoing research and preliminary results that apply evolutionary computation meth…
Millimeter-Wave NOMA with User Grouping, Power Allocation and Hybrid Beamforming
Lipeng Zhu, Jun Zhang, Zhenyu Xiao +3
The paper proposes a joint user grouping, power allocation, and hybrid beamforming scheme for downlink millimeter‑wave non‑orthogonal multiple access (mmWave‑NOMA) that improves su…
Training Multi-layer Spiking Neural Networks using NormAD based Spatio-Temporal Error Backpropagation
Navin Anwani, Bipin Rajendran
The paper proposes a training method for multi‑layer spiking neural networks that optimizes membrane potential deviations using a Normalized Approximate Descent algorithm, enabling…
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Jesus A. De Loera, Jamie Haddock, Anna Ma +1
The paper trains machine learning models to automatically select and tune optimization and signal processing algorithms, demonstrating improved performance for stochastic gradient…
Edge User Allocation with Dynamic Quality of Service
Phu Lai, Qiang He, Guangming Cui +6
The paper addresses the problem of allocating users to edge servers while allowing dynamic quality-of-service levels, proposing both an optimal algorithm and a fast heuristic to ma…