Add to ORKGAn improved particle swarm optimization algorithm is proposed and tested for two different test cases: surface fitting of a wing shape and an inverse design of an airfoil in subsonic flow. The new algorithm emphasizes the use of an indirect design prediction based on a local surrogate modeling as a part of update equations in particle swarm optimization algorithm structure. For all the demonstration problems considered herein, remarkable reductions in the computational times have been accomplished
This paper presents the results of applying direct and surrogate-based optimization (SBO) algorithms...
Liu Y, Liu J, Jin Y. Surrogate-Assisted Multipopulation Particle Swarm Optimizer for High-Dimensiona...
The surrogate-assisted optimization (SAO) process can utilize the knowledge contained in the surroga...
<p>Evolutionary algorithms cannot effectively handle computationally expensive problems because of t...
Like most evolutionary algorithms, particle swarm optimization (PSO) usually requires a large number...
This paper presents a study to design, analyze and optimize an airfoil trailing edge, i.e., shape mo...
Aerodynamic design, like many other engineering applications, is increasingly relying on computation...
Particle swarm optimization (PSO) is a population-based, heuristic minimization technique that is ba...
Particle swarm optimization (PSO) is a population-based, heuristic technique based on social behavio...
The paper proposes a global optimization algorithm employing surrogate modeling and adaptive infill ...
Function evaluations of many real-world optimization problems are time or resource consuming, posin...
Airfoil optimizations require costly high-fidelity solvers. By replacing the expensive solver with a...
Surrogate models have shown to be effective in assisting metaheuristic algorithms for solving comput...
Combining high precision numerical analysis methods with optimization algorithms to make a systemati...
Surrogate-based optimization and efficient global optimization in particular, is considered fo...
This paper presents the results of applying direct and surrogate-based optimization (SBO) algorithms...
Liu Y, Liu J, Jin Y. Surrogate-Assisted Multipopulation Particle Swarm Optimizer for High-Dimensiona...
The surrogate-assisted optimization (SAO) process can utilize the knowledge contained in the surroga...
<p>Evolutionary algorithms cannot effectively handle computationally expensive problems because of t...
Like most evolutionary algorithms, particle swarm optimization (PSO) usually requires a large number...
This paper presents a study to design, analyze and optimize an airfoil trailing edge, i.e., shape mo...
Aerodynamic design, like many other engineering applications, is increasingly relying on computation...
Particle swarm optimization (PSO) is a population-based, heuristic minimization technique that is ba...
Particle swarm optimization (PSO) is a population-based, heuristic technique based on social behavio...
The paper proposes a global optimization algorithm employing surrogate modeling and adaptive infill ...
Function evaluations of many real-world optimization problems are time or resource consuming, posin...
Airfoil optimizations require costly high-fidelity solvers. By replacing the expensive solver with a...
Surrogate models have shown to be effective in assisting metaheuristic algorithms for solving comput...
Combining high precision numerical analysis methods with optimization algorithms to make a systemati...
Surrogate-based optimization and efficient global optimization in particular, is considered fo...
This paper presents the results of applying direct and surrogate-based optimization (SBO) algorithms...
Liu Y, Liu J, Jin Y. Surrogate-Assisted Multipopulation Particle Swarm Optimizer for High-Dimensiona...
The surrogate-assisted optimization (SAO) process can utilize the knowledge contained in the surroga...