Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

Algorithm 3

Pseudocode of main body of the enhanced ABC algorithm.

(1)  Generate the initial population 𝑥_𝑖 based on chaotic maps and affinity strategy (𝑖=1,2,…,SN)

(2)  Evaluate the fitness (fit(𝑥_𝑖)) of the population

(3)  Set cycle to 1

(4)  Repeat

(5)  For each employed bee {

   Produce new solution 𝑣_𝑖 by using (7)

   Calculate its fitness value fit(𝑣_𝑖)

   Apply greedy selection process}

(6)   Adopt negative selection and network compression to eliminate redundant and similar food sources by using (18)

(7)   Randomly generate the same number of new individuals

(8)   Calculate the probability values 𝑃_𝑖 for the solution (𝑥_𝑖) by (16)

(9)   For each onlooker bee {

   Select a solution 𝑥_𝑖 depending on 𝑃_𝑖

   Produce new solution 𝑣_𝑗

   Calculate its fitness value fit(𝑣_𝑗)

   Apply greedy selection process}

(10)   If there is an abandoned solution for the scout,

   then replace it with a new solution which will be randomly produced by (4)

(11)  Memorize the best solution so far

(12)  Cycle = cycle + 1

(13)   Until cycle = MEN