function demo1%DEMO1  Demo for usage of DIFFERENTIALEVOLUTION.%		DEMO1 starts searching the minimum of Rosenbrock's saddle as a demo.%		Modify this function for your first optimization.%%		Markus Buehren%		Last modified 03.02.2008 %%		See also DIFFERENTIALEVOLUTION, ROSENBROCKSADDLE.% set titleoptimInfo.title = 'Demo 1 (Rosenbrock''s saddle)';% specify objective functionobjFctHandle = @rosenbrocksaddle;% define parameter names, ranges and quantization:paramDefCell = {	'parameter1', [-3 3], 0.01	'parameter2', [-3 3], 0.01};% 1. column: parameter names% 2. column: paramter ranges% 3. column: paramter quantizations% 4. column: initial values (optional)% set initial parameter values in struct objFctParams objFctParams.parameter1 =  -2;objFctParams.parameter2 = 2.5;% set single additional function parameterobjFctSettings = 100;% get default DE parametersDEParams = getdefaultparams;% set number of population members (often 10*D is suggested) DEParams.NP = 20;% do not use slave process hereDEParams.feedSlaveProc = 0;% set timesDEParams.maxiter       = 100;DEParams.maxtime       = 60;  % in secondsDEParams.maxclock      = [];% set display optionsDEParams.refreshiter   = 1;DEParams.refreshtime   = 10;  % in secondsDEParams.refreshtime2  = 20;  % in secondsDEParams.refreshtime3  = 40;  % in seconds% do not send E-mailsemailParams = [];% set random state in order to always use the same population members hererand('state', 1);% start differential evolution[bestmem, bestval, bestFctParams] = ...	differentialevolution(DEParams, paramDefCell, objFctHandle, ...	objFctSettings, objFctParams, emailParams, optimInfo); %#okdisp(' ');disp('Best parameter set returned by function differentialevolution:');disp(bestFctParams);