Research Article

Effect of Population Structures on Quantum-Inspired Evolutionary Algorithm

Algorithm 1

: Size of the population that is, number of individuals.
: Size of the Group that is, population is divided in groups.
: Size of the Problem being solved that is, number of variables.
: 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 .
: stores the Best solution of Group, , in the current (th) generation.
AR: Attractor Register that stores the attractor individual for every , where .
: current Global Best Solution.
begin
       t  = 0; assign , , ;
(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) stores the best solution in each Group, , into respective (t), j = 1,…,/;
(f) store the best solution b amongst (t);
        while (termination condition is not met) do
        begin
   t = t + 1;
(g)     select AR(t) according to migration condition;
(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)    store the best solution in each Group, , and (t1) into (t) respectively,
         j = 1,…,/;
(m)    store the best solution b amongst (t);
        end
end