Help, Matlab s pareto solution set of problems

c=[20019894805 200210597876 2003121110898]; b=[200199988510 20021131018712 20031201158015]; a(1,:,=c;a(2,:,=b;As a hint, the above functions can be easily implemented with the mean sum find function: sum(sum())find(max()) can be nested

Help, matlab pareto function drawing, the column chart with small values cannot be displayed 2011-05-15 11:23 low-key mad fish |Category:Mathematics I'm a beginner.,Please give me a lot of advice.**I use the following [i,j]=size....

c=[20019894805 200210597876 2003121110898]; b=[200199988510 20021131018712 20031201158015]; a(1,:,=c;a(2,:,=b;As a hint, the above functions can be easily implemented with the mean sum find function: sum(sum())find(max()) can be nested

[x,fval,attainfactor] =fgoalattain(fun,x0,goal,weight,a,b,aeq,beq,lb,ub,nonlcon)

x: optimal solution.

fval: the optimal value of each objective function.

attainfactor: the amount of fun:objective function that exceeds or does not reach the target, and since is a multi-objective function, this is a vector x0, the initial value of the independent variable.

goal: The goal is a vector.

weight: The weight of each objective.

The following three are the same as linear optimization.

ax<=b

aeq*x=beq

lbnonlcon is the same as in the nonlinear constraint function fmincon!

Do you have this program running for 40 hours, that long, if that's the case, there is a problem with your writing, I have seen a program written by someone before, and the result is out in less than a minute, it is four objective functions.

Hello, GA has made great progress in application, algorithm design, and basic theory, and is also widely used. In this paper, through the study of the basic genetic algorithm and its implementation in the multi-objective optimization problem, the research in the field of genetic algorithm is carried out, and the program is verified. In the study of multi-objective optimization problems, some of the methods adopted have obtained better Pareto solution sets in some examples.

As one of the powerful tools for solving global optimization problems, genetic algorithm is widely used, and is mainly used in the following fields:

1) Geneticbasemachinelearning based on genetic algorithmThis new learning mechanism brings hope to solve the bottleneck problem of knowledge acquisition and knowledge optimization and refining in artificial intelligence.

2) The interpenetration and combination of genetic algorithm and other computational intelligence methods.

3) The research on genetic algorithms for parallel processing is very active. This research is not only important for the development of genetic algorithms themselves, but also for the study of the new generation of intelligent computer architecture. (4) Application of genetic algorithm in the field of data mining.

The turnover rate of statistical personnel, expressed in terms of the pareto ratio, is calculated: the pareto ratio is the same as the employment rate!

Add a sentence at the end of the program:

axis([0 13 0 100]);

This web link is linked.

Such a result can be generated.

Do you have the data? I can write you a program to draw pareto graphics. Or, if you have any questions, you can talk about them. Please add a question.