An improved genetic algorithm and its application in neural network adversarial attack

  title={An improved genetic algorithm and its application in neural network adversarial attack},
  author={Dingming Yang and Zeyu Yu and Hong Yuan and Ya Ping Cui},
  journal={PLoS ONE},
The choice of crossover and mutation strategies plays a crucial role in the searchability, convergence efficiency and precision of genetic algorithms. In this paper, a novel improved genetic algorithm is proposed by improving the crossover and mutation operation of the simple genetic algorithm, and it is verified by 15 test functions. The qualitative results show that, compared with three other mainstream swarm intelligence optimization algorithms, the algorithm can not only improve the global… 


A new optimizer using particle swarm theory
  • R. Eberhart, J. Kennedy
  • Computer Science
    MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science
  • 1995
The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented
Particle swarm optimization
A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Neural Network Adversarial Attack Method Based on Improved Genetic Algorithm
A neural network adversarial attack method based on an improved genetic algorithm that improves the variation and crossover links based on the original genetic optimization algorithm, which greatly improves the iteration efficiency and shortens the running time.
Remora optimization algorithm
Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems
A new metaheuristic algorithm inspired by gorilla troops' social intelligence in nature, called Artificial Gorilla Troops Optimizer (GTO), in which gorillas' collective life is mathematically formulated, and new mechanisms are designed to perform exploration and exploitation.
An improved differential evolution algorithm and its application in optimization problem
In the proposed NBOLDE, the new evaluation parameters and weight factors are introduced into the neighborhood model to propose a new neighborhood strategy that has a faster convergence speed, higher convergence accuracy, and better optimization capabilities in solving high-dimensional complex functions.
Marine Predators Algorithm: A nature-inspired metaheuristic
Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm
The experimental results show that the proposed GFLHF-VRP and GAASAM can effectively solve the vehicle routing problem of the proposed model, achieve better performance than the genetic algorithm, and avoid falling into a local optimal trap.