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

Algorithm 2

Modified initialization step of ABC algorithm.

Set the population size SN, the number of randomly generated individuals SN_𝑟≫SN, the maximum number of chaotic

iterations 𝑁>200, the number of optimization parameters D, and the individual counter 𝑖=1, 𝑗=1

 {- -Chaotic systems- -}

 for  𝑖=1 to SN_𝑟  do

    for  𝑗=1 to D  do

       Randomly initialize the first chaotic variable cm_0,𝑗∈(0,1) and set iteration counter 𝑛=0

       for  𝑛=1 to N  do

          cm_𝑛+1,𝑗=2.3(cm_𝑛,𝑗)^{2sin(𝜋cm𝑛,𝑗)}

       end for

       𝑥^𝑗_𝑖=𝑥^𝑗_min+cm^𝑗_𝑛(𝑥^𝑗_max−𝑥^𝑗_min)

    end for

 end for

 {- - Affinity-based compression method- -}

 Set the threshold value 𝜉 and the individual counter 𝑖=1, 𝑗=1

 for  𝑖=1 to (SN_𝑟−1) do

     for  𝑘=𝑖+1 to SN_𝑟  do

       if  affinity(𝑥_𝑖,𝑥_𝑘)=∑^𝐷_𝑗=1(𝑥^𝑗_𝑖−𝑥^𝑗_𝑘)²<𝜉

           SN_𝑟=SN_𝑟−1, delete the individual 𝑘 in the population

       end if

    end for

 end for

 Selecting SN fittest individuals form set (𝑋(SN_𝑟)) as initial population