Kursawe
Problem definition
Objective function
a = 0.8
b = 3
f = @(x) [ sum(-10*exp(-0.2*sqrt(x(:,1:end-1).^2 + x(:,2:end).^2)),2),...
sum(abs(x).^a + 5*(sin(x.^b)),2)]
Optimization settings
o = struct% initializing struct
o.d = 3% dimension of decision variable
o.lb = -5% lower bounds
o.ub = 5% upper bounds
Problem properties
| dimension | objectives | smoothness |
| 3 | 2 | 0 |
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)