Kriging-assisted teaching-learning-based optimization (KTLBO) to solve computationally expensive constrained problems
H Dong, P Wang, C Fu, B Song - Information Sciences, 2021 - Elsevier
In this paper, a novel algorithm KTLBO is presented to achieve computationally expensive
constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated …
constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated …
Evolutionary algorithms for parameter optimization—thirty years later
Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …
developments in the field of evolutionary algorithms, with applications in parameter …
Partial evaluation strategies for expensive evolutionary constrained optimization
Constrained optimization problems (COPs) are frequently encountered in real-world design
applications. For some COPs, the evaluation of the objective (s) and/or constraint (s) may …
applications. For some COPs, the evaluation of the objective (s) and/or constraint (s) may …
Constrained multi-objective optimization with a limited budget of function evaluations
This paper proposes the Self-Adaptive algorithm for Multi-Objective Constrained
Optimization by using Radial Basis Function Approximations, SAMO-COBRA. This algorithm …
Optimization by using Radial Basis Function Approximations, SAMO-COBRA. This algorithm …
Constraint boundary pursuing-based surrogate-assisted differential evolution for expensive optimization problems with mixed constraints
Surrogate-assisted evolutionary algorithms have recently shown exceptional abilities for
handling with computationally Expensive Constrained Optimization Problems (ECOPs) …
handling with computationally Expensive Constrained Optimization Problems (ECOPs) …
SCGOSR: Surrogate-based constrained global optimization using space reduction
Global optimization problems with computationally expensive objective and constraints are
challenging. In this work, we present a new kriging-based constrained global optimization …
challenging. In this work, we present a new kriging-based constrained global optimization …
System architecture optimization strategies: dealing with expensive hierarchical problems
Choosing the right system architecture for the problem at hand is challenging due to the
large design space and high uncertainty in the early stage of the design process …
large design space and high uncertainty in the early stage of the design process …
SAMO-COBRA: a fast surrogate assisted constrained multi-objective optimization algorithm
This paper proposes a novel Self-Adaptive algorithm for Multi-Objective Constrained
Optimization by using Radial Basis Function Approximations, SAMO-COBRA. The algorithm …
Optimization by using Radial Basis Function Approximations, SAMO-COBRA. The algorithm …
Trust-region based adaptive radial basis function algorithm for global optimization of expensive constrained black-box problems
It has been a very challenging task to develop efficient and robust techniques to solve real-
world engineering optimization problems due to the unknown function properties, complex …
world engineering optimization problems due to the unknown function properties, complex …
An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses
V Mokarram, MR Banan - Applied Soft Computing, 2018 - Elsevier
Performance-based design (PBD) of buildings can be properly addressed in a multi-
objective optimization framework. However, computational costs of such an approach will be …
objective optimization framework. However, computational costs of such an approach will be …