Nature

Multi-Objective Evolutionary Optimization Techniques articles from across Nature Portfolio

Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...
BIOENGINEER

Deep Learning Meets Multi-Objective Optimization to Grade Vocational Teaching Quality

A new hybrid AI framework combining deep convolutional networks with multi-objective evolutionary optimization achieves 98.5 ...
Nature

Multi-Objective Optimization Methods in Engineering Design

Multi‐objective optimisation has emerged as a cornerstone in engineering design, addressing problems that involve simultaneous minimisation or maximisation of two or more conflicting objectives. At ...
FT Markets

WiMi Studies Quantum Encoding Circuit Adaptation Optimization Architecture Based on Reinforcement Learning

WiMi's proposed technical solution has its core innovations concentrated on the deep integration of model-based reinforcement learning algorithms and hierarchical circuit structures, constructing a ...