Swarm Intelligence Algorithms

20 Artificial Bee Colony Algorithm

where i ∈ {1, . . . , SN }, j ∈ {1, . . . , D}, D is the problem dimension, x

lb

j

and

x

ub

j

are the lower and upper bounds in jth dimension of design parameters,

respectively.

The food source population is evolved by the employed bees, onlooker

bees and scout bee phases based on swarm intelligence characteristics. In the

employed bees phase, the nectar exploitation behaviour is simulated by a local

search around each source i by Eq. 2.2.

ˆx

ij

= x

ij

+ φ

ij

(x

ij

− x

kj

) (2.2)

where k is a randomly chosen neighbour of ith solution and k ∈ {1, 2, . . . CS} :

k 6= i and φ

ij

is a real random number drawn from uniform distribu-

tion within ...