SchafferMO1
Problem definition
Objective function
f = @(x) [sum(x.^2,2), sum((x-2).^2,2)]
Optimization settings
o = struct% initializing struct
o.d = 3% dimension of decision variable
o.lb = -1000% lower bounds
o.ub = 1000% upper bounds
Problem properties
| dimension | objectives | smoothness |
| 3 | 2 | - |
Optimization example with nsga2
Algorithm options
o.maxit = 100% number of iterations
o.pop = 60% 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 = 4% frame frequency
info.animstart = 20% iteration to start animation
optimview('nsga2',info)