很好的遗传算法，能够解决很多优化问题，优化各种问题很好的遗传算法，能够解决很多优化问题，优化各种问题很好的遗传算法，能够解决很多...

% This script shows how to use the ga using a float representation. % You should see the demos for % more information as well. gademo1, gademo2, gademo3 global bounds % Setting the seed to the same for binary % rand('seed',sd) % Crossover Operators xFns = 'arithXover heuristicXover simpleXover'; xOpts = [1 0; 1 3; 1 0]; % Mutation Operators mFns = 'boundaryMutation multiNonUnifMutation nonUnifMutation unifMutation'; mOpts = [2 0 0;3 200 3;2 200 3;2 0 0]; % Termination Operators termFns = 'maxGenTerm'; termOps = [200]; % 200 Generations % Selection Function selectFn = 'normGeomSelect'; selectOps = [0.08]; % Evaluation Function evalFn = 'gaMichEval'; evalOps = []; type gaMichEval % Bounds on the variables bounds = [-3 12.1; 4.1 5.8]; % GA Options [epsilon float/binar display] gaOpts=[1e-6 1 1]; % Generate an intialize population of size 20 startPop = initialize(20,bounds,'gaMichEval',[1e-6 1]); % Lets run the GA pause [x endPop bestPop trace]=ga(bounds,evalFn,evalOps,startPop,gaOpts,... termFns,termOps,selectFn,selectOps,xFns,xOpts,mFns,mOpts); pause % x is the best solution found x pause % endPop is the ending population endPop pause % bestPop is the best solution tracked over generations bestPop pause % trace is a trace of the best value and average value of generations trace pause % Plot the best over time clg plot(trace(:,1),trace(:,2)); pause % Add the average to the graph hold on plot(trace(:,1),trace(:,3)); pause % Lets increase the population size by running the defaults % [x endPop bestPop trace]=ga(bounds,evalFn,evalOps,[],gaOpts); % x is the best solution found x pause % endPop is the ending population endPop pause % bestPop is the best solution tracked over generations bestPop pause % trace is a trace of the best value and average value of generations trace pause % Plot the best over time clg plot(trace(:,1),trace(:,2)); pause % Add the average to the graph hold on plot(trace(:,1),trace(:,3)); pause