Applied Multi-objective Optimization
Applied Multi-objective Optimization [electronic resource] /
edited by Nilanjan Dey.
- 1st ed. 2024.
- XI, 170 p. 60 illus., 45 illus. in color. online resource.
- Springer Tracts in Nature-Inspired Computing, 2524-5538 .
- Springer Tracts in Nature-Inspired Computing, .
Chapter 1 : An Introduction to Multi-objective Optimization using Meta-heuristic Algorithms: Techniques and Applications -- Chapter 2 : Counterfactual Explanations and Federated Learning for Multi-objective Optimization -- Chapter 3: Multi-objective Adaptive Guided Differential Evolution for Passively Controlled Structures Equipped with Tunned Mass Damper -- Chapter 4: Evolutionary Approaches for Multi-objective Optimization and Pareto-Optimal Solution Selection in Data Analytics -- Chapter 5 : Multi-objective Lichtenberg Algorithm for Optimum Design of Truss Structures -- Chapter 6 : Performance Analysis of Multi-objective Function-Based Fractional PID Controller for System Frequency Regulation -- Chapter 7: Multi-Modal Routing in Urban Transportation Networks using Multi-objective Quantum Particle Swarm -- Chapter 8 : Plant Leaf Disease Localization and Severity Measurement using Multi-objective Ant Colony Optimization -- Chapter 9 : Multi-objective Feature Selection: A Comprehensive Review -- Chapter 10 :Enhancing Feature Selection using Multi-objective Optimization Concept.
The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science. .
9789819703531
Computational intelligence.
Mathematical optimization.
Algorithms.
Computational Intelligence.
Optimization.
Algorithms.
Q342
006.3
Chapter 1 : An Introduction to Multi-objective Optimization using Meta-heuristic Algorithms: Techniques and Applications -- Chapter 2 : Counterfactual Explanations and Federated Learning for Multi-objective Optimization -- Chapter 3: Multi-objective Adaptive Guided Differential Evolution for Passively Controlled Structures Equipped with Tunned Mass Damper -- Chapter 4: Evolutionary Approaches for Multi-objective Optimization and Pareto-Optimal Solution Selection in Data Analytics -- Chapter 5 : Multi-objective Lichtenberg Algorithm for Optimum Design of Truss Structures -- Chapter 6 : Performance Analysis of Multi-objective Function-Based Fractional PID Controller for System Frequency Regulation -- Chapter 7: Multi-Modal Routing in Urban Transportation Networks using Multi-objective Quantum Particle Swarm -- Chapter 8 : Plant Leaf Disease Localization and Severity Measurement using Multi-objective Ant Colony Optimization -- Chapter 9 : Multi-objective Feature Selection: A Comprehensive Review -- Chapter 10 :Enhancing Feature Selection using Multi-objective Optimization Concept.
The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science. .
9789819703531
Computational intelligence.
Mathematical optimization.
Algorithms.
Computational Intelligence.
Optimization.
Algorithms.
Q342
006.3
