Numerical and Evolutionary Optimization 2021

• Other Authors: Quiroz, Marcela (Editor), de la Fraga, Luis Gerardo (Editor), Lara, Adriana (Editor), Trujillo, Leonardo (Editor), Schütze, Oliver (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Information technology industries; Computer science; distributor's pallet loading problem; heuristics; bin packing; real-life instances; emergency medical services; emergency medicine; decision-support system; pre-hospital emergency care; ambulance response time; machine learning; geo-indistinguishability; differential privacy; privacy-preserving machine learning; input perturbation; estimation of distribution algorithm; Mallows model; moth-flame algorithm; job shop scheduling problem; quay crane scheduling problem; first-passage time; Markov chain; queueing theory; simulation; OR in health services; KPI; wind energy; wind turbine blades; erosion; modal analysis; aerodynamic analysis; AutoML; feature selection; fault severity assessment; gearboxes; XGBoost classifiers; autism; attention; ASD; learning activities; EEG; BCI; features; artificial intelligence; Grouping Genetic Algorithm; variable decomposition; Large-Scale Constrained Optimization; DVT; early diagnosis; machine-learning; smart system; embedded system; edge computing; edge device; OpenFOAM; CFD; ANFIS; ANFIS (GA); ANFIS (PSO); ANFIS (FFA); nonlinear programming; largest small polygons (LSP); {LSP(n)} model-class; optimal area sequence {A(n)}; revised LSP model; mathematica model development environment; IPOPT solver engine; numerical optimization results and regression model for estimating {A(n)}; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

This reprint was established after the 9th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.