A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network
Table 1
Description of parameters.
Parameters
Description
Number of individuals
The number of individuals is equal to the sum of the employed bees and following bees. The number of employed bees is equal to the number of following bees
Number of iterations
Optimization times of algorithm
Number of food source
The number of food source is equal to the number of employed bees. A food source represents a solution of clustering problem
Limit
Number of times when there is search honey source
Number of groups
A population can be divided into several sub-memeplexes
Number of local iterations
Optimization times of local search
Weight of pheromone
The pheromones released by ant: it determines the selection of path
Weight of heuristic information
It determines the possibility that the ant will take the path before it chooses
