Numerical and Evolutionary Optimization 2020

Download Url(s)
https://mdpi.com/books/pdfview/book/4195Contributor(s)
Quiroz, Marcela (editor)
Schütze, Oliver (editor)
Ruiz, Juan Gabriel (editor)
de la Fraga, Luis Gerardo (editor)
Language
EnglishAbstract
This book was established after the 8th 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.
Keywords
robust optimization; differential evolution; ROOT; optimization framework; drainage rehabilitation; overflooding; pipe breaking; VCO; CMOS differential pair; PVT variations; Monte Carlo analysis; multi-objective optimization; Pareto Tracer; continuation; constraint handling; surrogate modeling; multiobjective optimization; evolutionary algorithms; kriging method; ensemble method; adaptive algorithm; liquid storage tanks; base excitation; artificial intelligence; Multi-Gene Genetic Programming; computational fluid dynamics; finite volume method; JSSP; CMOSA; CMOTA; chaotic perturbation; fixed point arithmetic; FP16; pseudo random number generator; incorporation of preferences; multi-criteria classification; decision-making process; multi-objective evolutionary optimization; outranking relationships; decision maker profile; profile assessment; region of interest approximation; optimization using preferences; hybrid evolutionary approach; forecasting; Convolutional Neural Network; LSTM; COVID-19; deep learning; trust region methods; multiobjective descent; derivative-free optimization; radial basis functions; fully linear models; decision making process; cognitive tasks; recommender system; project portfolio selection problem; usability evaluation; multi-objective portfolio optimization problem; trapezoidal fuzzy numbers; density estimators; steady state algorithms; protein structure prediction; Hybrid Simulated Annealing; Template-Based Modeling; structural biology; Metropolis; optimization; linear programming; energy centralWebshop link
https://mdpi.com/books/pdfview ...ISBN
9783036516691, 9783036516707Publisher website
www.mdpi.com/booksPublication date and place
Basel, Switzerland, 2021Classification
Research and information: general
Mathematics and Science