Strategy optimization for range gate pull-off track-deception jamming under black-box circumstance
Y Wang, T Zhang, L Kong, Z Ma - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, we study the strategy optimization problem of black-box range gate pull-off
(RGPO) jamming. In the black-box RGPO jamming, the jammer does not have extensive …
(RGPO) jamming. In the black-box RGPO jamming, the jammer does not have extensive …
Optimal computing budget allocation for particle swarm optimization in stochastic optimization
Particle swarm optimization (PSO) is a popular metaheuristic for deterministic optimization.
Originated in the interpretations of the movement of individuals in a bird flock or fish school …
Originated in the interpretations of the movement of individuals in a bird flock or fish school …
Opposition-based hybrid strategy for particle swarm optimization in noisy environments
Particle swarm optimization (PSO) is a population-based algorithm designed to tackle
various optimization problems. However, its performance deteriorates significantly when …
various optimization problems. However, its performance deteriorates significantly when …
A new particle swarm optimization algorithm for noisy optimization problems
We propose a new particle swarm optimization algorithm for problems where objective
functions are subject to zero-mean, independent, and identically distributed stochastic noise …
functions are subject to zero-mean, independent, and identically distributed stochastic noise …
Population statistics for particle swarm optimization: Resampling methods in noisy optimization problems
Abstract Particle Swarm Optimization (PSO) is a metaheuristic whose performance
deteriorates significantly when utilized on optimization problems subject to noise. On these …
deteriorates significantly when utilized on optimization problems subject to noise. On these …
An opposition-based particle swarm optimization algorithm for noisy environments
MC Zhou, Z Zhao, C **ong… - 2018 IEEE 15th …, 2018 - ieeexplore.ieee.org
Particle Swarm Optimization (PSO) is a population-based algorithm designed to tackle
various optimization problems. However, its performance deteriorates significantly when …
various optimization problems. However, its performance deteriorates significantly when …
Particle swarm optimization with neighborhood-based budget allocation
The standard particle swarm optimization (PSO) algorithm allocates the total available
budget of function evaluations equally and concurrently among the particles of the swarm. In …
budget of function evaluations equally and concurrently among the particles of the swarm. In …
Fibonacci multi-modal optimization algorithm in noisy environment
X Wang, Y Wang, H Wu, L Gao, L Luo, P Li, X Shi - Applied Soft Computing, 2020 - Elsevier
Noises are very common in practical optimization problems. It will cause interference on
optimization algorithms and thus makes the algorithms difficult to find a true global extreme …
optimization algorithms and thus makes the algorithms difficult to find a true global extreme …
A learning automata-based particle swarm optimization algorithm for noisy environment
JQ Zhang, LW Xu, J Ma… - 2015 IEEE Congress on …, 2015 - ieeexplore.ieee.org
Particle Swarm Optimization (PSO) is an outstanding evolutionary algorithm designed to
tackle various optimization problems. However, its performance deteriorates significantly in …
tackle various optimization problems. However, its performance deteriorates significantly in …
Noisy optimization by evolution strategies with online population size learning
Optimization modeling of real-world application problems usually involves noise from
various sources. Noisy optimization imposes challenges to optimization methods since the …
various sources. Noisy optimization imposes challenges to optimization methods since the …