Bukin6
Problem definition
Objective function
f = @(x) 100*sqrt(abs(x(:,2) - 0.01*x(:,1).^2)) + 0.01*(abs(x(:,1) + 10))
Optimization settings
o = struct% initializing struct
o.lb = [-15 -3]% lower bounds
o.ub = [-5 3]% upper bounds
Graphic representation
[x,y] = meshgrid(-15:0.5:-5, -3:0.2:3) surf(x,y,f([x(:),y(:)]))
Problem properties
| convexity | smoothness | minimum |
| 0 | 0 | f(-10,1) = 0 |
Optimization example with fminsearch
Optimization
rng(0)% for tractability
x0 = [-9.2,3]% initial guess
[xmin,fmin,info] = fminsearch(f,x0,o)% running minimization
Animation
rng(0) x0 = [-9.2,3] [~,~,info] = fminsearch(f,x0,o) info.sol = [-10 1 0]% solution
info.animate = true% plot animation
info.animfreq = 5% frame frequency
info.np = [21 31]% number of points for meshgrid
optimview('fminsearch',info)
References
[1] S.K. Mishra, "Some New Test Functions for Global Optimization and Performance of Repulsive Particle Swarm Methods", North-Eastern Hill University, India, 2002