constr
Problem definition
Objective function
f = @(x) [x(:,1), (1+x(:,2))./x(:,1)]
Optimization settings
o = struct% initializing struct
g1 = @(x) x(:,2) + 9*x(:,1) - 6 g2 = @(x) -x(:,2) + 9*x(:,1) - 1 o.g = @(x) g1(x).*(g1(x)<0) + g2(x).*(g2(x)<0)% constraints
o.d = 2% dimension of decision variable
o.lb = [0.1 0]% lower bounds
o.ub = [1 5]% upper bounds
Problem properties
dimension | objectives | smoothness |
2 | 2 | - |
Optimization example with nsga2
Algorithm options
o.maxit = 40% 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
rng(0) [~,~,~,~,~,info] = nsga2(f,o) info.plot = 'pareto' info.animate = true% plot animation
info.animfreq = 2% frame frequency
optimview('nsga2',info)