A Novel Particle Swarm Optimization Algorithm for Global Optimization

Algorithm 1

Framework of NPSO. Remark: in our algorithm, for simplicity, in (8), we can set , which can meet our needs.

(1) Initialize a population of particles with random positions in a given search space, and random

  velocities ; the maximum iteration ; ; ; the length of chaotic sequence .

(2) Set and find .

(3) while do

(4)

(5) for to do

(6)  for to do

(7)   By (3) and (4), update the velocity of each particle.

(8)   By (5), update the position of each particle.

(9)  end for

(10)   if

(11)    , set ;

(12)   else

(13)   set .

(14)  end if

(15)  if

(16)   set ,

(17)  end if

(18) end for

(19) for to do

(20)  if

(21)   By (8), to generate a new position, and replace .

(22)  end if

(23) end for

(24) By (9)–(12), to chaotic search in , and update (if necessary).

(25)

(26) end while