% OBJECTIVE FUNCTION
f = @(x) [4*sum(x.^2,2), ...
       sum((x-5).^2,2)]

% OPTIMIZATION SETTINGS
o = struct	% initializing struct 
g1 = @(x) 25 - (x(:,1)-5).^2 - x(:,2).^2
g2 = @(x) (x(:,1)-8).^2 + (x(:,2)+3).^2 - 7.7
o.g = @(x) g1(x).*(g1(x)<0) + g2(x).*(g2(x)<0)	% constraints
o.d = 2	% dimension of decision variable
o.lb = [0 0]	% lower bounds
o.ub = [5 3]	% upper bounds

% ALGORITHM OPTIONS

o.maxit = 6	% number of iterations 
o.pop = 40	% number of population 

% OPTIMIZATION 
rng(0)	% for tractability 
[popPos,popFront,popCost,popInfo,traceIt] = nsga2(f,o)	% running minimization  

% ANIMATION
% Uncomment the following code to generate animation % 
% rng(0)
% [~,~,~,~,~,info] = nsga2(f,o)
% info.plot = 'pareto'
% info.animate = true	% plot animation 
% optimview('nsga2',info)