Answered

Correct implementation of multi start option with pre-specified starters

If you read the description of MultiStart run, you see that calling run(ms,problem,k)) uses k - 1 random points in addition to t...

Correct implementation of multi start option with pre-specified starters

If you read the description of MultiStart run, you see that calling run(ms,problem,k)) uses k - 1 random points in addition to t...

1 year ago | 0

| accepted

Answered

Matlab Code Assistance for Multistart or GA

Perhaps more relevant documentation is here: MultiStart with lsqnonlin, Problem-Based MultiStart Using lsqcurvefit or lsqnonli...

Matlab Code Assistance for Multistart or GA

Perhaps more relevant documentation is here: MultiStart with lsqnonlin, Problem-Based MultiStart Using lsqcurvefit or lsqnonli...

1 year ago | 0

Answered

Multistart apparently does not respect the supplied initial points

The only error here is your expectation that fmincon always converges to the closest local minimum. It does not. fun = @(x) x.^...

Multistart apparently does not respect the supplied initial points

The only error here is your expectation that fmincon always converges to the closest local minimum. It does not. fun = @(x) x.^...

1 year ago | 0

| accepted

Answered

How to create a Triple Objective Genetic Algorithm establish constraints and plot 3D

You are confusing many things here. The first thing you have to do is decide if you are using optimization variables, meaning t...

How to create a Triple Objective Genetic Algorithm establish constraints and plot 3D

You are confusing many things here. The first thing you have to do is decide if you are using optimization variables, meaning t...

1 year ago | 1

Answered

Unrecognized function or variable 'options'. for simulannealbnd, but works for fminunc

optimoptions requires that the first argument be the name of the solver. Something like options = optimoptions('simulannealbnd'...

Unrecognized function or variable 'options'. for simulannealbnd, but works for fminunc

optimoptions requires that the first argument be the name of the solver. Something like options = optimoptions('simulannealbnd'...

1 year ago | 0

| accepted

Answered

When the genetic algorithm has integer constraint issues, how to customize the variogram to eliminate the ignored warning

I am not sure what you mean by "variogram." But I think that I know the reason for your difficulty. As the Release Notes state, ...

When the genetic algorithm has integer constraint issues, how to customize the variogram to eliminate the ignored warning

I am not sure what you mean by "variogram." But I think that I know the reason for your difficulty. As the Release Notes state, ...

1 year ago | 0

| accepted

Answered

Optimization terminated: maximum number of generations exceeded.

ga exceeded 200 generations. If you want more, increase the MaxGenerations option. options = optimoptions('ga','ConstraintToler...

Optimization terminated: maximum number of generations exceeded.

ga exceeded 200 generations. If you want more, increase the MaxGenerations option. options = optimoptions('ga','ConstraintToler...

1 year ago | 1

| accepted

Answered

How to output additional variables from objective function using ga optimization?

I am not sure what you are trying to do. You might be trying to pass intermediate values calculated within ga to reuse, for exam...

How to output additional variables from objective function using ga optimization?

I am not sure what you are trying to do. You might be trying to pass intermediate values calculated within ga to reuse, for exam...

1 year ago | 0

Answered

Multiple initial points in fmincon optimization

fmincon takes the size of the x0 input as determining the number of input variables. Your x0 has 6 elements, so fmincon thinks t...

Multiple initial points in fmincon optimization

fmincon takes the size of the x0 input as determining the number of input variables. Your x0 has 6 elements, so fmincon thinks t...

1 year ago | 0

| accepted

Answered

hi, urgent help

There is an example of using MultiStart for problem-based lsqnonlin here: https://www.mathworks.com/help/gads/fit-function-usin...

hi, urgent help

There is an example of using MultiStart for problem-based lsqnonlin here: https://www.mathworks.com/help/gads/fit-function-usin...

1 year ago | 0

Answered

Integer optimization returns decimal numbers

The intlinprog solver (which solve calls internally for MILP problems) does not necessarily return or use internally exact integ...

Integer optimization returns decimal numbers

The intlinprog solver (which solve calls internally for MILP problems) does not necessarily return or use internally exact integ...

1 year ago | 0

Answered

Genetic Algorithm output is different than manual calculation

The issue is that your objective function varies extremely quickly, with about 10000 squiggles per unit near x = 1. The exponent...

Genetic Algorithm output is different than manual calculation

The issue is that your objective function varies extremely quickly, with about 10000 squiggles per unit near x = 1. The exponent...

1 year ago | 1

Answered

Differential equation fit to my data: incorrect minimization

I think that you probably did not set up your problem correctly. There are relevant documentation examples: https://www.mathwor...

Differential equation fit to my data: incorrect minimization

I think that you probably did not set up your problem correctly. There are relevant documentation examples: https://www.mathwor...

1 year ago | 0

Answered

Swarmsize to give to particleswarm optimization

For most optimization problems, as opposed to algorithm development, the question is how to obtain a good solution in as few fun...

Swarmsize to give to particleswarm optimization

For most optimization problems, as opposed to algorithm development, the question is how to obtain a good solution in as few fun...

1 year ago | 0

Answered

Output function for Simulated Anealing

You have mistaken the output of optimoptions for the optimvalues structure in simulate annealing. opts = optimoptions("simulann...

Output function for Simulated Anealing

You have mistaken the output of optimoptions for the optimvalues structure in simulate annealing. opts = optimoptions("simulann...

1 year ago | 0

Answered

Optimisation of batch time using genetic algorithm and ODE solver

I do not know what the batch time and crystal size mean in your model, so I cannot tell you directly what to do. I can tell you...

Optimisation of batch time using genetic algorithm and ODE solver

I do not know what the batch time and crystal size mean in your model, so I cannot tell you directly what to do. I can tell you...

1 year ago | 0

Answered

surrogateopt multi-objective function output

I do not understand why you want to use surrogateopt to help solve a multiobjective problem. I think that gamultiobj or paretose...

surrogateopt multi-objective function output

I do not understand why you want to use surrogateopt to help solve a multiobjective problem. I think that gamultiobj or paretose...

1 year ago | 0

Answered

GA initial solution not used in problem base solver

When using the problem-based approach you must pass initial points to ga using optimvalues. See https://www.mathworks.com/help/r...

GA initial solution not used in problem base solver

When using the problem-based approach you must pass initial points to ga using optimvalues. See https://www.mathworks.com/help/r...

1 year ago | 0

Answered

How to solve TSP using GA?

I think that it is useless to try to solve a TSP using ga, mainly because ga is so slow and unreliable compared to Optimization ...

How to solve TSP using GA?

I think that it is useless to try to solve a TSP using ga, mainly because ga is so slow and unreliable compared to Optimization ...

1 year ago | 0

Answered

What is the difference between surrogateopt and bayeopt?

The algorithms have fairly complete descriptions: https://www.mathworks.com/help/stats/bayesian-optimization-algorithm.html ht...

What is the difference between surrogateopt and bayeopt?

The algorithms have fairly complete descriptions: https://www.mathworks.com/help/stats/bayesian-optimization-algorithm.html ht...

1 year ago | 0

Answered

Unrecognized field name "ProblemdefOptions".

It sounds as if you are using the problem-based approach. To do so, you might need to specify some options when you call solve, ...

Unrecognized field name "ProblemdefOptions".

It sounds as if you are using the problem-based approach. To do so, you might need to specify some options when you call solve, ...

1 year ago | 0

Answered

How to plot non-quadratic functions?

This sounds like a multiobjective optimization problem. See Generate and Plot Pareto Front and, if you have Global Optimization ...

How to plot non-quadratic functions?

This sounds like a multiobjective optimization problem. See Generate and Plot Pareto Front and, if you have Global Optimization ...

1 year ago | 0

Answered

How do I iterate f(x)

Is this what you are looking for? f = @(x)exp(x) - 2 - x - x.^2./2; t = linspace(0,5); plot(t,f(t)) OK, there is a root in t...

How do I iterate f(x)

Is this what you are looking for? f = @(x)exp(x) - 2 - x - x.^2./2; t = linspace(0,5); plot(t,f(t)) OK, there is a root in t...

1 year ago | 0

Answered

How do I solve this system of non-linear equations using fsolve?

I don't know if this is helpful, but I suspected that fsolve was having trouble because of the scaling of your variables; everyt...

How do I solve this system of non-linear equations using fsolve?

I don't know if this is helpful, but I suspected that fsolve was having trouble because of the scaling of your variables; everyt...

1 year ago | 0

Answered

How to display the value of a specific component of the objective function after computation is done?

I'd be very interested to know what you think of the nuclear fuel disposal example. But to answer your question, let's look at ...

How to display the value of a specific component of the objective function after computation is done?

I'd be very interested to know what you think of the nuclear fuel disposal example. But to answer your question, let's look at ...

1 year ago | 0

| accepted

Answered

How to make the initial population in genetic algorithm fixed?

In addition to what Walter said, you can set the global random seed. rng default % Or rng(seed) [x,fval] = solve(problem,"Solv...

How to make the initial population in genetic algorithm fixed?

In addition to what Walter said, you can set the global random seed. rng default % Or rng(seed) [x,fval] = solve(problem,"Solv...

1 year ago | 1

| accepted

Answered

Setting Pareto FronI want to set the Pareto Front using genetic algorithm

You can take a larger population. For example, options = optimoptions('gamultiobj','PopulationSize',300); Make sure to pass op...

Setting Pareto FronI want to set the Pareto Front using genetic algorithm

You can take a larger population. For example, options = optimoptions('gamultiobj','PopulationSize',300); Make sure to pass op...

1 year ago | 0

Answered

Gamultiobj takes too long to run. Is there a workaround?

I am sorry, but I do not have time to understand your model in detail. However, I notice that you are using the problem-based ap...

Gamultiobj takes too long to run. Is there a workaround?

I am sorry, but I do not have time to understand your model in detail. However, I notice that you are using the problem-based ap...

1 year ago | 0

| accepted

Answered

how to solve a multi-objective nonlinear optimization problem with constraints ?

For an example that optimizes the solution of an ODE using optimization variables, see Fit ODE Parameters using Optimization Var...

how to solve a multi-objective nonlinear optimization problem with constraints ?

For an example that optimizes the solution of an ODE using optimization variables, see Fit ODE Parameters using Optimization Var...

1 year ago | 0

| accepted

Answered

Which optimization method is better for problems with random steps

In addition to what the other answerers have described, there does exist an optimization solver that can deal with stochastic ob...

Which optimization method is better for problems with random steps

In addition to what the other answerers have described, there does exist an optimization solver that can deal with stochastic ob...

1 year ago | 0