Algorithm 1. Random Contrastive Interaction (RCI)

Input:

t: global optimum position

T: Matrix of population information

N: population size

fit: Matrix of objective function valuesx: Position of the population

Output:

X*: Matrix of newly generated stock information

The number of individuals TS to be selected for this iteration is calculated according to Equation (4);

1.      rs = randperm(N, TS); %Generate non-repeating individual subscripts based on TS.

2.      [af, bf] = sort(fit); % af is the result of the ascending order of the fitness values and bf is the corresponding subscript position.

3.      db = find(bf == rs(1));Find the location of the optimal individual in rs.

4.      dw = find(bf == rs(TS));Find the worst individual position in rs.

5.      dbest = pos(bbb(db),:);

6.      dworst = pos(bbb(dw),:);

7.      For i = 1:size(rs,2)

8.          For j = 1:size(x,2)

9.              Calculate the corresponding new position in rs according to Equation (3).

10.          End

11.      End

Return X*