R solver optimization
I am new to R solver and I want to have a simple example in R for the below problem:
I have four columns which I calculate the individual sums as the illustrated sample example below:
The problem I want to solve in R:
Find the optimal lines that satisfies, simultaneously, the below statements:
- For the first two columns (a, b) the individual summations to be more close to 0
- The sums of (c, d) to be more close to 5
I do not have restrictions of which package solver to use. It could be helpful to have an example of R code for this!
EDIT
For the same solution I would like to apply some rules:
- I want the sum(c) > sum(d) AND sum(d) < (static number, like 5)
- Also, if I want the sums to fall into a range of numbers and not just static numbers, how the solution could it be written?
r optimization solver
asked Nov 23 '18 at 10:39
VamkosVamkos
425
add a comment |
I am new to R solver and I want to have a simple example in R for the below problem:
I have four columns which I calculate the individual sums as the illustrated sample example below:
The problem I want to solve in R:
Find the optimal lines that satisfies, simultaneously, the below statements:
- For the first two columns (a, b) the individual summations to be more close to 0
- The sums of (c, d) to be more close to 5
I do not have restrictions of which package solver to use. It could be helpful to have an example of R code for this!
EDIT
For the same solution I would like to apply some rules:
- I want the sum(c) > sum(d) AND sum(d) < (static number, like 5)
- Also, if I want the sums to fall into a range of numbers and not just static numbers, how the solution could it be written?
r optimization solver
asked Nov 23 '18 at 10:39
VamkosVamkos
425
1
I've foundNlcOptimnice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf
– Jonny Phelps
Nov 23 '18 at 11:30
1
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04
add a comment |
I am new to R solver and I want to have a simple example in R for the below problem:
I have four columns which I calculate the individual sums as the illustrated sample example below:
The problem I want to solve in R:
Find the optimal lines that satisfies, simultaneously, the below statements:
- For the first two columns (a, b) the individual summations to be more close to 0
- The sums of (c, d) to be more close to 5
I do not have restrictions of which package solver to use. It could be helpful to have an example of R code for this!
EDIT
For the same solution I would like to apply some rules:
- I want the sum(c) > sum(d) AND sum(d) < (static number, like 5)
- Also, if I want the sums to fall into a range of numbers and not just static numbers, how the solution could it be written?
r optimization solver
asked Nov 23 '18 at 10:39
VamkosVamkos
425
I am new to R solver and I want to have a simple example in R for the below problem:
I have four columns which I calculate the individual sums as the illustrated sample example below:
The problem I want to solve in R:
Find the optimal lines that satisfies, simultaneously, the below statements:
- For the first two columns (a, b) the individual summations to be more close to 0
- The sums of (c, d) to be more close to 5
I do not have restrictions of which package solver to use. It could be helpful to have an example of R code for this!
EDIT
For the same solution I would like to apply some rules:
- I want the sum(c) > sum(d) AND sum(d) < (static number, like 5)
- Also, if I want the sums to fall into a range of numbers and not just static numbers, how the solution could it be written?
r optimization solver
r optimization solver
asked Nov 23 '18 at 10:39
VamkosVamkos
425
asked Nov 23 '18 at 10:39
VamkosVamkos
425
edited Nov 24 '18 at 13:02
Vamkos
asked Nov 23 '18 at 10:39
VamkosVamkos
425
asked Nov 23 '18 at 10:39
VamkosVamkos
425
asked Nov 23 '18 at 10:39
VamkosVamkos
425
425
1
I've foundNlcOptimnice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf
– Jonny Phelps
Nov 23 '18 at 11:30
1
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04
add a comment |
1
I've foundNlcOptimnice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf
– Jonny Phelps
Nov 23 '18 at 11:30
1
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04
1
1
I've found
NlcOptim nice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf– Jonny Phelps
Nov 23 '18 at 11:30
I've found
NlcOptim nice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf– Jonny Phelps
Nov 23 '18 at 11:30
1
1
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04
add a comment |
1 Answer
1
active
oldest
votes
Using M defined reproducibly in the Note at the end we find the b which minimizes the following objective where b is a 0/1 vector:
sum((b %*% M - c(0, 0, 5, 5))^2)
1) CVXR Using the CVXR package we get a solution c(1, 0, 0, 1, 1) which means choose rows 1, 4 and 5.
library(CVXR)
b <- Bool(n)
pred <- t(b) %*% M
y <- c(0, 0, 5, 5)
objective <- Minimize(sum((t(y) - pred)^2))
problem <- Problem(objective)
soln <- solve(problem)
bval <- soln$getValue(b)
zapsmall(c(bval))
## [1] 1 0 0 1 1
2) Brute Force Alternately since there are only 5 rows there are only 2^5 possible solutions so we can try them all and pick the one which minimizes the objective. First we compute a matrix solns with 2^5 columns such that each column is one possible solution. Then we compute the objective function for each column and take the one which minimizes it.
n <- nrow(M)
inverse.which <- function(ix, n) replace(integer(n), ix, 1)
L <- lapply(0:n, function(i) apply(combn(n, i), 2, inverse.which, n))
solns <- do.call(cbind, L)
pred <- t(t(solns) %*% M)
obj <- colSums((pred - c(0, 0, 5, 5))^2)
solns[, which.min(obj)]
## [1] 1 0 0 1 1
Note
M <- matrix(c(.38, -.25, .78, .83, -.65,
.24, -.35, .44, -.88, .15,
3, 5, 13, -15, 18,
18, -7, 23, -19, 7), 5)
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column inpredand the corresponding column insolnsthat violates the constraint.
– G. Grothendieck
Nov 24 '18 at 13:03
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53445096%2fr-solver-optimization%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Using M defined reproducibly in the Note at the end we find the b which minimizes the following objective where b is a 0/1 vector:
sum((b %*% M - c(0, 0, 5, 5))^2)
1) CVXR Using the CVXR package we get a solution c(1, 0, 0, 1, 1) which means choose rows 1, 4 and 5.
library(CVXR)
b <- Bool(n)
pred <- t(b) %*% M
y <- c(0, 0, 5, 5)
objective <- Minimize(sum((t(y) - pred)^2))
problem <- Problem(objective)
soln <- solve(problem)
bval <- soln$getValue(b)
zapsmall(c(bval))
## [1] 1 0 0 1 1
2) Brute Force Alternately since there are only 5 rows there are only 2^5 possible solutions so we can try them all and pick the one which minimizes the objective. First we compute a matrix solns with 2^5 columns such that each column is one possible solution. Then we compute the objective function for each column and take the one which minimizes it.
n <- nrow(M)
inverse.which <- function(ix, n) replace(integer(n), ix, 1)
L <- lapply(0:n, function(i) apply(combn(n, i), 2, inverse.which, n))
solns <- do.call(cbind, L)
pred <- t(t(solns) %*% M)
obj <- colSums((pred - c(0, 0, 5, 5))^2)
solns[, which.min(obj)]
## [1] 1 0 0 1 1
Note
M <- matrix(c(.38, -.25, .78, .83, -.65,
.24, -.35, .44, -.88, .15,
3, 5, 13, -15, 18,
18, -7, 23, -19, 7), 5)
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column inpredand the corresponding column insolnsthat violates the constraint.
– G. Grothendieck
Nov 24 '18 at 13:03
add a comment |
Using M defined reproducibly in the Note at the end we find the b which minimizes the following objective where b is a 0/1 vector:
sum((b %*% M - c(0, 0, 5, 5))^2)
1) CVXR Using the CVXR package we get a solution c(1, 0, 0, 1, 1) which means choose rows 1, 4 and 5.
library(CVXR)
b <- Bool(n)
pred <- t(b) %*% M
y <- c(0, 0, 5, 5)
objective <- Minimize(sum((t(y) - pred)^2))
problem <- Problem(objective)
soln <- solve(problem)
bval <- soln$getValue(b)
zapsmall(c(bval))
## [1] 1 0 0 1 1
2) Brute Force Alternately since there are only 5 rows there are only 2^5 possible solutions so we can try them all and pick the one which minimizes the objective. First we compute a matrix solns with 2^5 columns such that each column is one possible solution. Then we compute the objective function for each column and take the one which minimizes it.
n <- nrow(M)
inverse.which <- function(ix, n) replace(integer(n), ix, 1)
L <- lapply(0:n, function(i) apply(combn(n, i), 2, inverse.which, n))
solns <- do.call(cbind, L)
pred <- t(t(solns) %*% M)
obj <- colSums((pred - c(0, 0, 5, 5))^2)
solns[, which.min(obj)]
## [1] 1 0 0 1 1
Note
M <- matrix(c(.38, -.25, .78, .83, -.65,
.24, -.35, .44, -.88, .15,
3, 5, 13, -15, 18,
18, -7, 23, -19, 7), 5)
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column inpredand the corresponding column insolnsthat violates the constraint.
– G. Grothendieck
Nov 24 '18 at 13:03
add a comment |
Using M defined reproducibly in the Note at the end we find the b which minimizes the following objective where b is a 0/1 vector:
sum((b %*% M - c(0, 0, 5, 5))^2)
1) CVXR Using the CVXR package we get a solution c(1, 0, 0, 1, 1) which means choose rows 1, 4 and 5.
library(CVXR)
b <- Bool(n)
pred <- t(b) %*% M
y <- c(0, 0, 5, 5)
objective <- Minimize(sum((t(y) - pred)^2))
problem <- Problem(objective)
soln <- solve(problem)
bval <- soln$getValue(b)
zapsmall(c(bval))
## [1] 1 0 0 1 1
2) Brute Force Alternately since there are only 5 rows there are only 2^5 possible solutions so we can try them all and pick the one which minimizes the objective. First we compute a matrix solns with 2^5 columns such that each column is one possible solution. Then we compute the objective function for each column and take the one which minimizes it.
n <- nrow(M)
inverse.which <- function(ix, n) replace(integer(n), ix, 1)
L <- lapply(0:n, function(i) apply(combn(n, i), 2, inverse.which, n))
solns <- do.call(cbind, L)
pred <- t(t(solns) %*% M)
obj <- colSums((pred - c(0, 0, 5, 5))^2)
solns[, which.min(obj)]
## [1] 1 0 0 1 1
Note
M <- matrix(c(.38, -.25, .78, .83, -.65,
.24, -.35, .44, -.88, .15,
3, 5, 13, -15, 18,
18, -7, 23, -19, 7), 5)
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
Using M defined reproducibly in the Note at the end we find the b which minimizes the following objective where b is a 0/1 vector:
sum((b %*% M - c(0, 0, 5, 5))^2)
1) CVXR Using the CVXR package we get a solution c(1, 0, 0, 1, 1) which means choose rows 1, 4 and 5.
library(CVXR)
b <- Bool(n)
pred <- t(b) %*% M
y <- c(0, 0, 5, 5)
objective <- Minimize(sum((t(y) - pred)^2))
problem <- Problem(objective)
soln <- solve(problem)
bval <- soln$getValue(b)
zapsmall(c(bval))
## [1] 1 0 0 1 1
2) Brute Force Alternately since there are only 5 rows there are only 2^5 possible solutions so we can try them all and pick the one which minimizes the objective. First we compute a matrix solns with 2^5 columns such that each column is one possible solution. Then we compute the objective function for each column and take the one which minimizes it.
n <- nrow(M)
inverse.which <- function(ix, n) replace(integer(n), ix, 1)
L <- lapply(0:n, function(i) apply(combn(n, i), 2, inverse.which, n))
solns <- do.call(cbind, L)
pred <- t(t(solns) %*% M)
obj <- colSums((pred - c(0, 0, 5, 5))^2)
solns[, which.min(obj)]
## [1] 1 0 0 1 1
Note
M <- matrix(c(.38, -.25, .78, .83, -.65,
.24, -.35, .44, -.88, .15,
3, 5, 13, -15, 18,
18, -7, 23, -19, 7), 5)
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
edited Nov 23 '18 at 14:53
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
answered Nov 23 '18 at 13:34
G. GrothendieckG. Grothendieck
148k10131236
148k10131236
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column inpredand the corresponding column insolnsthat violates the constraint.
– G. Grothendieck
Nov 24 '18 at 13:03
add a comment |
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column inpredand the corresponding column insolnsthat violates the constraint.
– G. Grothendieck
Nov 24 '18 at 13:03
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
Thank you for your answer!! Two additional questions. If I want to have some rules for the same results, for example the sum of column c to be bigger than sum of column d, how could it be written? Second: If for the sum i do not want to have a static number like 3, 5 etc but a wide range like (5 - 8), how could it be written?
– Vamkos
Nov 24 '18 at 12:44
1
1
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column in
pred and the corresponding column in solns that violates the constraint.– G. Grothendieck
Nov 24 '18 at 13:03
CVXR will continue to work provided your revised objective and added constraints maintain the convexity of the problem. See the CVXR documentation. For the brute force method you can modify the objective as desired and you can simply remove any column in
pred and the corresponding column in solns that violates the constraint.– G. Grothendieck
Nov 24 '18 at 13:03
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53445096%2fr-solver-optimization%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
1
I've found
NlcOptimnice to use. Very flexible once you get the hang of it and is quick. cran.r-project.org/web/packages/NlcOptim/NlcOptim.pdf– Jonny Phelps
Nov 23 '18 at 11:30
1
Please do not use images to show your data. It means that anyone who answers has to retype all the data to run their code. Use text instead. I have done it this time for you in my answer.
– G. Grothendieck
Nov 23 '18 at 14:26
@G.Grothendieck Thanks for the advice!
– Vamkos
Nov 24 '18 at 12:23
Very helpful! Thank you @JonnyPhelps
– Vamkos
Nov 24 '18 at 13:04