Optimization of truss structures using multi-objective cheetah optimizer
In this study, a multi-objective version of the recently proposed cheetah optimizer called
multi-objective cheetah optimizer (MOCO) has been proposed. MOCO draws inspiration …
multi-objective cheetah optimizer (MOCO) has been proposed. MOCO draws inspiration …
Deep neural operators as accurate surrogates for shape optimization
Deep neural operators, such as DeepONet, have changed the paradigm in high-
dimensional nonlinear regression, paving the way for significant generalization and speed …
dimensional nonlinear regression, paving the way for significant generalization and speed …
Evolving to multi-modal knowledge graphs for engineering design: state-of-the-art and future challenges
With the support of advanced information and communication technologies and open
innovative design platforms, the emerging and blooming paradigm of mass personalization …
innovative design platforms, the emerging and blooming paradigm of mass personalization …
Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm
This paper introduces a novel approach, the Modified Electric Eel Foraging Optimization
(EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic …
(EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic …
Optimum design of a composite drone component using slime mold algorithm
Composite materials have a wide range of applications in many industries due to their
manufacturability, high strength values, and light filling. The sector where composite …
manufacturability, high strength values, and light filling. The sector where composite …
Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components
This paper introduces and investigates an enhanced Partial Reinforcement Optimization
Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory …
Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory …
Protein multiple conformation prediction using multi-objective evolution algorithm
The breakthrough of AlphaFold2 and the publication of AlphaFold DB represent a significant
advance in the field of predicting static protein structures. However, AlphaFold2 models tend …
advance in the field of predicting static protein structures. However, AlphaFold2 models tend …
Experimental and numerical investigation of crash performances of additively manufactured novel multi-cell crash box made with CF15PET, PLA, and ABS
In this study, a novel multi-cell crash box was designed and produced using 15% short
carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), and …
carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), and …
Enhancing the performance of a additive manufactured battery holder using a coupled artificial neural network with a hybrid flood algorithm and water wave algorithm
BS Yildiz - Materials Testing, 2024 - degruyter.com
This research is the first attempt in the literature to combine design for additive
manufacturing and hybrid flood algorithms for the optimal design of battery holders of an …
manufacturing and hybrid flood algorithms for the optimal design of battery holders of an …
An efficient hybrid multi-objective optimization method coupling global evolutionary and local gradient searches for solving aerodynamic optimization problems
F Cao, Z Tang, C Zhu, X Zhao - Mathematics, 2023 - mdpi.com
Aerodynamic shape optimization is frequently complicated and challenging due to the
involvement of multiple objectives, large-scale decision variables, and expensive cost …
involvement of multiple objectives, large-scale decision variables, and expensive cost …