SchafferMO2
Problem definition
Objective function
f = @(x) [-x.*(x<=1) + (x-2).*(x>1 & x<=3) + (4-x).*(x>3 & x<=4) + (x-4).*(x>4), ...
(x-5).^2]
Optimization settings
o = struct% initializing struct
o.d = 1% dimension of decision variable
o.lb = -5% lower bounds
o.ub = 10% upper bounds
Problem properties
| dimension | objectives | smoothness |
| 1 | 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)