Research Article

Effect of Population Structures on Quantum-Inspired Evolutionary Algorithm

Algorithm 2

: Size of the population that is, number of individuals.
: Size of the Problem being solved that is, number of variables.
: Number of Rows
: Number of Columns
: Generation Counter.
: th -bit that stores the value of their and .
: th Quantum Individual comprising of their , where .
: Quantum Register that comprises of all the Quantum individuals, , where .
: th binary bit that stores the value of 0 or 1 formed by collapsing corresponding .
: th Binary Individual comprising of their , where .
: Binary Register that comprises of all the Binary individuals, , where .
: stores the best solution of all the Binary individuals, , where .
: Attractor Register that stores the attractor individual for every , where .
: current Global Best Solution.
NL: List of neighbors of all the individuals, , where .
Begin
  t  = 0; assign , , A, B;
(a) initialize Q(t);
(b) make P(t) by observing the states of Q(t);
(c) evaluate P(t);
(d) store the best solutions among P(t) into B(t);
(e) compute NL;
(f) store the best solution b amongst B(t);
       while (termination condition is not met) do
       begin
   t  = t + 1;
(g)   select AR(t);
(h)   update Q(t1) according to P(t1) and AR(t) using Q-gates;
(i)   make P(t) by observing the states of Q(t);
(j)   evaluate P(t);
(k)   store the best solutions among P(t) and B(t1) into B(t);
(l)   stores the best solution b amongst B(t);
       end
end