Multi-objective evolutionary algorithmThe image classificationFor neural architecture search, NSGA-Net has searched a representative neural architecture set of Pareto-optimal solutions to consider both accuracy and computation complexity simultaneously. However, some decision-makers only concentrate on such ...
This paper described an optimization methodology based on a combination of an Artificial Neural Network and a Multiobjective Evolutionary Algorithm. First, the ANN was trained and validated using simulation results. The database of cases was created using Latin Hypercube sampling, and GenOpt automation...
In this paper, we propose a multi-objective evolutionary algorithm for automatic deep neural architecture search. The algorithm optimizes the performance of the model together with the number of network parameters. This allows exploring architectures that are both successful and compact. We test the ...
Dragonfly Algorithm (NSDA)60, a reference vector based multiobjective evolutionary algorithm with Q-learning for operator adaptation61, a many-objective evolutionary algorithm based on hybrid dynamic decomposition62 and use of two penalty values in multiobjective evolutionary algorithm based on ...
Deb, K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester Deb, K, Pratap, A, Agarwal, S, Meyarivan, T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6: pp. 182-197 CrossRef Druckmann, S, Banitt, Y, Gide...
Multi-objective optimization in WEDM of D3 tool steel using integrated approach of Taguchi method amp; Grey relational analysis A hybrid evolutionary algorithm with adaptive multi-population strategy for multi-objective optimization problems Multi-objective shape optimization of a plate-fin heat exchanger ...
In 2007, Zhang and Li19–21 proposed an algorithm, a Multi-Objective Evolutionary Algorithm based on Decomposition MOEA/D). However, research on MOEA/D has revealed that some, but not all, solutions are chosen in several sub-problems (Fig. 1), which may result in loss of population ...
optimizationparallelmulti-objectivequality-diversity UpdatedFeb 8, 2025 Python A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS) macosiosmachine-learningobjective-cneural-networkregressionrankingsupervised-learningalgorithm-implementationsmulti-objective ...
A new method for Modular Neural Network optimization based on a Multi-objective Hierarchical Genetic Algorithm is proposed in this paper. The modular neural network using a granular approach and its optimization using a multi-objective hierarchical genetic algorithm provides better results than when the...
objective evolutionary algorithm, it is necessary to satisfy three conditions: (1) the algorithm has good convergence; (2) the algorithm has a good distribution of the solution set on both the decision space and the objective space; and (3) the algorithm is able to find more equivalent PSs....