MOGBO: A new Multiobjective Gradient-Based Optimizer for real-world structural optimization problems
To handle the multiobjective optimization problems of truss-bar design, this paper introduces
a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based …
a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based …
A hyper-heuristic guided by a probabilistic graphical model for single-objective real-parameter optimization
Metaheuristics algorithms are designed to find approximate solutions for challenging
optimization problems. The success of the algorithm over a given optimization task relies on …
optimization problems. The success of the algorithm over a given optimization task relies on …
Pareto dominance based multiobjective cohort intelligence algorithm
MV Patil, AJ Kulkarni - Information Sciences, 2020 - Elsevier
In the recent days, several novel and specialized algorithms are coming up for solving
particular class of problems. However, their performance on new benchmark or real-world …
particular class of problems. However, their performance on new benchmark or real-world …
Enhanced decomposition-based hybrid evolutionary and gradient-based algorithm for many-objective optimization
P Mohammad Zadeh, M Mohagheghi - Applied Intelligence, 2023 - Springer
This paper presents a novel decomposition-based hybrid many-objective optimization
method using particle swarm optimization (PSO) and sequential quadratic programming …
method using particle swarm optimization (PSO) and sequential quadratic programming …
A Bayesian based Hyper-Heuristic approach for global optimization
D Oliva, MSR Martins - 2019 IEEE Congress on Evolutionary …, 2019 - ieeexplore.ieee.org
Several metaheuristics have been developed for global optimization. Most of them are
designed for solving a specific problem at hand, and their use on a new implementation is a …
designed for solving a specific problem at hand, and their use on a new implementation is a …
Optimization of groundwater pumping and river-aquifer exchanges for management of water resources
Multi-objective optimization problems can be solved through Simulation-Optimization (SO)
techniques where the pareto front gives the optimal solutions in the problem domains …
techniques where the pareto front gives the optimal solutions in the problem domains …
Leveraging Gaussian process regression and many-objective optimization through voting scores for fault identification
Using piezoelectric impedance/admittance sensing for structural health monitoring is
promising, owing to the simplicity in circuitry design as well as the high-frequency …
promising, owing to the simplicity in circuitry design as well as the high-frequency …
Data Sampling and Reasoning: Harnessing Optimization and Machine Learning for Design and System Identification
P Cao - 2018 - digitalcommons.lib.uconn.edu
The recently rapid advancements in sensing devices and computational power have caused
paradigm shift in engineering analyses: data driven and sampling-based approaches play …
paradigm shift in engineering analyses: data driven and sampling-based approaches play …
Identifying structural damage with data driven impedance response calibration
The impedance/admittance measurements of a piezoelectric transducer circuit bonded to or
embedded in a host structure can be used as damage indicator, since damage will introduce …
embedded in a host structure can be used as damage indicator, since damage will introduce …
[PDF][PDF] Leveraging Gaussian Process Calibration and Many-Objective Evaluation for Fault Identification with Impedance Responses
P Cao, Q Shuai, J Tang - researchgate.net
the impedance/admittance measurements of a piezoelectric transducer circuit bonded to a
host structure can be used as damage indicator because the present of damage will …
host structure can be used as damage indicator because the present of damage will …