Numerical and Evolutionary Optimization 2020
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 th...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (364 p.) |
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Quiroz, Marcela edt Numerical and Evolutionary Optimization 2020 Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (364 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier 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. English Research & information: general bicssc Mathematics & science bicssc 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 central 3-0365-1669-7 3-0365-1670-0 Schütze, Oliver edt Ruiz, Juan Gabriel edt de la Fraga, Luis Gerardo edt Quiroz, Marcela oth Schütze, Oliver oth Ruiz, Juan Gabriel oth de la Fraga, Luis Gerardo oth |
| language |
English |
| format |
eBook |
| author2 |
Schütze, Oliver Ruiz, Juan Gabriel de la Fraga, Luis Gerardo Quiroz, Marcela Schütze, Oliver Ruiz, Juan Gabriel de la Fraga, Luis Gerardo |
| author_facet |
Schütze, Oliver Ruiz, Juan Gabriel de la Fraga, Luis Gerardo Quiroz, Marcela Schütze, Oliver Ruiz, Juan Gabriel de la Fraga, Luis Gerardo |
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m q mq o s os j g r jg jgr l f l g d lflg lflgd |
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HerausgeberIn HerausgeberIn HerausgeberIn Sonstige Sonstige Sonstige Sonstige |
| title |
Numerical and Evolutionary Optimization 2020 |
| spellingShingle |
Numerical and Evolutionary Optimization 2020 |
| title_full |
Numerical and Evolutionary Optimization 2020 |
| title_fullStr |
Numerical and Evolutionary Optimization 2020 |
| title_full_unstemmed |
Numerical and Evolutionary Optimization 2020 |
| title_auth |
Numerical and Evolutionary Optimization 2020 |
| title_new |
Numerical and Evolutionary Optimization 2020 |
| title_sort |
numerical and evolutionary optimization 2020 |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2021 |
| physical |
1 electronic resource (364 p.) |
| isbn |
3-0365-1669-7 3-0365-1670-0 |
| illustrated |
Not Illustrated |
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