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Difference Vector Angle Dominance with an Angle Threshold for Expensive Multi-objective Optimization
For the latest two years, relation classification-based surrogate-assisted algorithms show good potential for solving expensive multi-objective...
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A hybrid-model optimization algorithm based on the Gaussian process and particle swarm optimization for mixed-variable CNN hyperparameter automatic search
Convolutional neural networks (CNNs) have been developed quickly in many real-world fields. However, CNN’s performance depends heavily on its...
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Image Signal Processor Parameter Tuning with Surrogate-Assisted Particle Swarm Optimization
Evolutionary algorithms (EA) are developed and compared based on well defined benchmark problems, but their application to real-world problems is...
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A sequential constraints updating approach for Kriging surrogate model-assisted engineering optimization design problem
Kriging surrogate model has been widely used in engineering design optimization problems to replace computational cost simulations. To facilitate the...
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Wall-Cor Net: wall color replacement via Clifford chance-based deep generative adversarial network
Color design for interior circumstance is a challenging area due to the numerous aspects that must be matched. Although learning from images is a...
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Pareto-Based Bi-indicator Infill Sampling Criterion for Expensive Multiobjective Optimization
Infill sampling criteria play a crucial role in saving expensive evaluations for surrogate-assisted multiobjective evolutionary algorithms. Promoting...
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Eliminating Non-dominated Sorting from NSGA-III
The series of non-dominated sorting based genetic algorithms (NSGA-series) has clearly shown their niche in solving multi- and many-objective...
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Optimally Weighted Ensembles for Efficient Multi-objective Optimization
The process of industrial design engineering is often involved with the simultaneous optimization of multiple expensive objectives. The surrogate...
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Efficiency Improvement with Multi-fidelity Surrogates
This chapter introduces how to use multi-fidelity models to improve the training efficiency of genetic programming for dynamic flexible job shop...
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Surrogate model assisted cooperative coevolution for large scale optimization
It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a...
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Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization
In the past decades, a number of surrogate-assisted evolutionary algorithms (SAEAs) have been developed to solve expensive multiobjective...
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A Surrogate-Assisted Improved Many-Objective Evolutionary Algorithm
The many-objective evolutionary algorithm is an effective method to tackle many-objective optimization problems. We improve the two-archive2...
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Investigating Normalization Bounds for Hypervolume-Based Infill Criterion for Expensive Multiobjective Optimization
While solving expensive multi-objective optimization problems, there may be stringent limits on the number of allowed function evaluations. Surrogate...
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Genetic Programming for Production Scheduling An Evolutionary Learning Approach
This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
Design of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with...
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High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
Bayesian Optimization (BO) is a surrogate-based global optimization strategy that relies on a Gaussian Process regression (GPR) model to approximate...
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Efficient computational system reliability analysis of reinforced soil-retaining structures under seismic conditions including the effect of simulated noise
This article presents a computational reliability analysis of reinforced soil-retaining structures (RSRS) under seismic conditions. The internal...
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Variable-fidelity hypervolume-based expected improvement criteria for multi-objective efficient global optimization of expensive functions
Variable-fidelity surrogate-based efficient global optimization (EGO) method with the ability to adaptively select low-fidelity (LF) and...
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Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem
Combinatorial optimization problems can involve computationaly expensive fitness function, making their resolution challenging. Surrogate models are...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Networks
Designing microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for...