Numerical and Evolutionary Optimization 2024
This Special Issue was inspired by the 11th International Workshop on Numerical and Evolutionary Optimization (NEO 2024), held from 3 to 6 September 2024 in Mexico City, Mexico, and hosted by Cinvestav. Solving real-world scientific and engineering problems has always been a challenge, and the compl...
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| Aineistotyyppi: | Online |
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| Kieli: | englanti |
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MDPI - Multidisciplinary Digital Publishing Institute
2026
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| Linkit: | ONIX_20260416T142754_9783725855759_42 |
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| collection | Directory of Open Access Books |
| description | This Special Issue was inspired by the 11th International Workshop on Numerical and Evolutionary Optimization (NEO 2024), held from 3 to 6 September 2024 in Mexico City, Mexico, and hosted by Cinvestav. Solving real-world scientific and engineering problems has always been a challenge, and the complexity of these tasks has increased in recent years as more sources of data and information have been continuously developed. Thus, the design and analysis of powerful search and optimization techniques is of great importance. Two well-established fields that focus on this task are (i) traditional numerical optimization techniques and (ii) bio-inspired metaheuristic methods. Both of these general approaches have unique strengths and weaknesses, allowing researchers to solve certain challenging problems while failing to solve others. The goal of the NEO workshop series is to gather experts from both fields to discuss, compare, and merge these complementary perspectives. Collaborative work allows researchers to maximize the strengths and minimize the weaknesses of both paradigms. NEO also intends to help researchers in these fields to understand and tackle real-world problems like pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. |
| format | Online |
| id | doab-20.500.12854ir-174837 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1748372026-04-16T16:41:57Z Numerical and Evolutionary Optimization 2024 Quiroz, Marcela Cuate, Oliver Trujillo, Leonardo Schütze, Oliver Adaptive observer Nonlinear system Lipschitz nonlinearities Feature selection Differential evolution Cost reduction Multi-objective optimization Cardiovascular system Heart diseases Pressure–volume loops Normal form Sliding mode observer Fault detection and isolation Unobservable states Accelerometry Physical activity Artificial neural networks Radius of curvature Classification models Human activity recognition Self-balancing inverted pendulum Controller design TS system Trajectory tracking Image enhancement Contrast and detail Sigmoid transformation NSGA-II A posterior preference articulation Memetic algorithm Particle swarm Technique diversification Improved local search Internet shopping problem Adaptive adjustment Branch and bound Pipeline diagnosis Leak detection Water monitoring Neuro-fuzzy system Zonotopic Kalman filter Sensor faults Generalized dynamic observer Denial-of-service attack (DoS) False data injection attack (FDI) Random data injection attack (RDI) Cyber–physical system Takagi–Sugeno system (T-S) Markovian logic Vision Transformer (ViT) Weld defect detection Computer vision in manufacturing Automated welding inspection Multiclass classification Bin packing problem Grouping genetic algorithm Mutation operator Adaptive control Investment portfolios Optimization Forecast Heuristics CO2 Air quality Remote monitoring Forecasting Artificial neural network Mixed no-idle permutation flow shop scheduling Evolutionary strategy Generalized Mallows model Estimation of distribution algorithm Diabetes mellitus model Nonlinear analysis Thau observer Insulin observation Compact invariant sets Content distribution networks Evolutionary algorithms Cloud computing Climate change Multivariate time series Deep learning Principal component analysis Ensemble methods Particle swarm optimization N A thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology This Special Issue was inspired by the 11th International Workshop on Numerical and Evolutionary Optimization (NEO 2024), held from 3 to 6 September 2024 in Mexico City, Mexico, and hosted by Cinvestav. Solving real-world scientific and engineering problems has always been a challenge, and the complexity of these tasks has increased in recent years as more sources of data and information have been continuously developed. Thus, the design and analysis of powerful search and optimization techniques is of great importance. Two well-established fields that focus on this task are (i) traditional numerical optimization techniques and (ii) bio-inspired metaheuristic methods. Both of these general approaches have unique strengths and weaknesses, allowing researchers to solve certain challenging problems while failing to solve others. The goal of the NEO workshop series is to gather experts from both fields to discuss, compare, and merge these complementary perspectives. Collaborative work allows researchers to maximize the strengths and minimize the weaknesses of both paradigms. NEO also intends to help researchers in these fields to understand and tackle real-world problems like pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. 2026-04-16T16:41:51Z 2026-04-16T16:41:51Z 2025 book ONIX_20260416T142754_9783725855759_42 9783725855759 9783725855766 https://directory.doabooks.org/handle/20.500.12854/174837 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/11716 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-5576-6 10.3390/books978-3-7258-5576-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725855759 9783725855766 354 CH open access |
| spellingShingle | Adaptive observer Nonlinear system Lipschitz nonlinearities Feature selection Differential evolution Cost reduction Multi-objective optimization Cardiovascular system Heart diseases Pressure–volume loops Normal form Sliding mode observer Fault detection and isolation Unobservable states Accelerometry Physical activity Artificial neural networks Radius of curvature Classification models Human activity recognition Self-balancing inverted pendulum Controller design TS system Trajectory tracking Image enhancement Contrast and detail Sigmoid transformation NSGA-II A posterior preference articulation Memetic algorithm Particle swarm Technique diversification Improved local search Internet shopping problem Adaptive adjustment Branch and bound Pipeline diagnosis Leak detection Water monitoring Neuro-fuzzy system Zonotopic Kalman filter Sensor faults Generalized dynamic observer Denial-of-service attack (DoS) False data injection attack (FDI) Random data injection attack (RDI) Cyber–physical system Takagi–Sugeno system (T-S) Markovian logic Vision Transformer (ViT) Weld defect detection Computer vision in manufacturing Automated welding inspection Multiclass classification Bin packing problem Grouping genetic algorithm Mutation operator Adaptive control Investment portfolios Optimization Forecast Heuristics CO2 Air quality Remote monitoring Forecasting Artificial neural network Mixed no-idle permutation flow shop scheduling Evolutionary strategy Generalized Mallows model Estimation of distribution algorithm Diabetes mellitus model Nonlinear analysis Thau observer Insulin observation Compact invariant sets Content distribution networks Evolutionary algorithms Cloud computing Climate change Multivariate time series Deep learning Principal component analysis Ensemble methods Particle swarm optimization N A thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Numerical and Evolutionary Optimization 2024 |
| title | Numerical and Evolutionary Optimization 2024 |
| title_full | Numerical and Evolutionary Optimization 2024 |
| title_fullStr | Numerical and Evolutionary Optimization 2024 |
| title_full_unstemmed | Numerical and Evolutionary Optimization 2024 |
| title_short | Numerical and Evolutionary Optimization 2024 |
| title_sort | numerical and evolutionary optimization 2024 |
| topic | Adaptive observer Nonlinear system Lipschitz nonlinearities Feature selection Differential evolution Cost reduction Multi-objective optimization Cardiovascular system Heart diseases Pressure–volume loops Normal form Sliding mode observer Fault detection and isolation Unobservable states Accelerometry Physical activity Artificial neural networks Radius of curvature Classification models Human activity recognition Self-balancing inverted pendulum Controller design TS system Trajectory tracking Image enhancement Contrast and detail Sigmoid transformation NSGA-II A posterior preference articulation Memetic algorithm Particle swarm Technique diversification Improved local search Internet shopping problem Adaptive adjustment Branch and bound Pipeline diagnosis Leak detection Water monitoring Neuro-fuzzy system Zonotopic Kalman filter Sensor faults Generalized dynamic observer Denial-of-service attack (DoS) False data injection attack (FDI) Random data injection attack (RDI) Cyber–physical system Takagi–Sugeno system (T-S) Markovian logic Vision Transformer (ViT) Weld defect detection Computer vision in manufacturing Automated welding inspection Multiclass classification Bin packing problem Grouping genetic algorithm Mutation operator Adaptive control Investment portfolios Optimization Forecast Heuristics CO2 Air quality Remote monitoring Forecasting Artificial neural network Mixed no-idle permutation flow shop scheduling Evolutionary strategy Generalized Mallows model Estimation of distribution algorithm Diabetes mellitus model Nonlinear analysis Thau observer Insulin observation Compact invariant sets Content distribution networks Evolutionary algorithms Cloud computing Climate change Multivariate time series Deep learning Principal component analysis Ensemble methods Particle swarm optimization N A thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | Adaptive observer Nonlinear system Lipschitz nonlinearities Feature selection Differential evolution Cost reduction Multi-objective optimization Cardiovascular system Heart diseases Pressure–volume loops Normal form Sliding mode observer Fault detection and isolation Unobservable states Accelerometry Physical activity Artificial neural networks Radius of curvature Classification models Human activity recognition Self-balancing inverted pendulum Controller design TS system Trajectory tracking Image enhancement Contrast and detail Sigmoid transformation NSGA-II A posterior preference articulation Memetic algorithm Particle swarm Technique diversification Improved local search Internet shopping problem Adaptive adjustment Branch and bound Pipeline diagnosis Leak detection Water monitoring Neuro-fuzzy system Zonotopic Kalman filter Sensor faults Generalized dynamic observer Denial-of-service attack (DoS) False data injection attack (FDI) Random data injection attack (RDI) Cyber–physical system Takagi–Sugeno system (T-S) Markovian logic Vision Transformer (ViT) Weld defect detection Computer vision in manufacturing Automated welding inspection Multiclass classification Bin packing problem Grouping genetic algorithm Mutation operator Adaptive control Investment portfolios Optimization Forecast Heuristics CO2 Air quality Remote monitoring Forecasting Artificial neural network Mixed no-idle permutation flow shop scheduling Evolutionary strategy Generalized Mallows model Estimation of distribution algorithm Diabetes mellitus model Nonlinear analysis Thau observer Insulin observation Compact invariant sets Content distribution networks Evolutionary algorithms Cloud computing Climate change Multivariate time series Deep learning Principal component analysis Ensemble methods Particle swarm optimization N A thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20260416T142754_9783725855759_42 |