An overview of intelligent optimization Algorithms __ Intelligent Optimization algorithm

Inspired by the laws of human intelligence, biological community or natural phenomena, many intelligent optimization algorithms have been invented, which mainly include:

(1) Genetic algorithm: imitating the biological evolution mechanism of nature

(2) Differential Evolution algorithm: Optimizing Search through cooperation and competition among groups of individuals

(3) Immune algorithm: Simulated biological immune system learning and cognitive function

(4) Ant colony algorithm: simulating ant collective path behavior

(5) Particle swarm algorithm: Simulating the behavior of birds and fish groups

(6) Simulated annealing algorithm: from the solid material annealing process

(7) Tabu search algorithm: Simulating the process of human mental memory

(8) Neural network algorithm: Simulated animal neural network behavioral characteristics

Generally can be divided into the following five categories:

(1) Evolutionary class algorithm:

Genetic algorithm, Differential evolution algorithm, immune algorithm

(2) Swarm intelligence algorithm

Ant colony Algorithm and particle swarm optimization algorithm

(3) Simulated annealing algorithm

(4) Tabu search algorithm

(5) Neural Network algorithm