With Trelea, Common, and Clerc types along with ...
% ND Alpine function, described by Clerc...
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
% f(x) = sum( abs(x.*sin(x) + 0.1.*x) )
% x = N element row vector containing [x0, x1, ..., xN]
% each row is processed independently,
% you can feed in matrices of timeXN no prob
% example: cost = alpine([1,2;5,6;0,-50])
% note: known minimum =0 @ all x = 0
% Brian Birge
% Rev 1.0
out = sum(abs(in.*sin(in) + 0.1.*in),2);