Research Article

Clone Chaotic Parallel Evolutionary Algorithm for Low-Energy Clustering in High-Density Wireless Sensor Networks

Table 1

Description of parameters.

ParametersDescription

Number of individualsAn individual represents a solution to a low-energy clustering problem
Number of iterationsAlgorithm optimization times
Mutation rateProbability of binary code mutation
Crossover rateProbability of binary change exchange between two individuals
Learning factors C1 and C2Acceleration constant, normally, C1 = C2 = 2
Maximum velocity of the particleMaximum speed of particle movement
The initial temperatureA sufficiently large temperature defined before the first iteration
The annealing temperature coefficientCooling rate coefficient, when the cooling rate coefficient is smaller, the cooling rate is faster