Convex approximation of the non-convex functionIs the following function convex-$cap$?Is there any method that convert a non-convex problem to a convex one?is the Superellipse function convex or not?Gradient descent with box constraints and possible non-convex function.What is the solution of this convex optimization problem?positive constant divided by a concave function, how to convexify this constraint?Interesting Global Minimum of a Non-convex FunctionChange of variable (convex optimization)Non-convex Constraint Satisfaction problemIs it possible to “solve” iterative (convex/non-convex) optimization problems via learning (one-shot)?

Does "every" first-order theory have a finitely axiomatizable conservative extension?

How do I go from 300 unfinished/half written blog posts, to published posts?

Tiptoe or tiphoof? Adjusting words to better fit fantasy races

Is expanding the research of a group into machine learning as a PhD student risky?

How to be diplomatic in refusing to write code that breaches the privacy of our users

How do I rename a Linux host without needing to reboot for the rename to take effect?

What can we do to stop prior company from asking us questions?

I'm in charge of equipment buying but no one's ever happy with what I choose. How to fix this?

Anatomically Correct Strange Women In Ponds Distributing Swords

You cannot touch me, but I can touch you, who am I?

Sequence of Tenses: Translating the subjunctive

Proof of work - lottery approach

Lay out the Carpet

How does Loki do this?

Where does the Z80 processor start executing from?

Go Pregnant or Go Home

Why escape if the_content isnt?

Is there a good way to store credentials outside of a password manager?

Do sorcerers' subtle spells require a skill check to be unseen?

How to Reset Passwords on Multiple Websites Easily?

What is paid subscription needed for in Mortal Kombat 11?

Is this version of a gravity generator feasible?

Unreliable Magic - Is it worth it?

Do all network devices need to make routing decisions, regardless of communication across networks or within a network?



Convex approximation of the non-convex function


Is the following function convex-$cap$?Is there any method that convert a non-convex problem to a convex one?is the Superellipse function convex or not?Gradient descent with box constraints and possible non-convex function.What is the solution of this convex optimization problem?positive constant divided by a concave function, how to convexify this constraint?Interesting Global Minimum of a Non-convex FunctionChange of variable (convex optimization)Non-convex Constraint Satisfaction problemIs it possible to “solve” iterative (convex/non-convex) optimization problems via learning (one-shot)?













0












$begingroup$


I have the following constraint for the optimization problem in hand:



$$fracb_klog_2 left(1 + fracp_k alpha_ksum_j neq k p_j alpha_j + sum_n sum_l Xi_n,l,k 2^-2 v_n,l right) + 2 fracsum_n sum_l v_n,l C_F leq epsilon$$



where the variables are $v_n,l$, $p_k$, $p_j, ; j neq k$. The constants are $alpha_k$, $alpha_j$, $b_k$, $C_F$, $Xi_n,l,k$.



The constraint is non-convex in $v_n,l, p_k, p_j, ; j neq k$. I am looking solve the problem with sucessive convex approximation approach.



I need some suggestion on feasibilty of the problem in terms of it if its possible to have a convex approximation for the above constraint and or suggest some method to solve it.










share|cite|improve this question











$endgroup$







  • 1




    $begingroup$
    The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
    $endgroup$
    – Rodrigo de Azevedo
    15 hours ago






  • 2




    $begingroup$
    Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
    $endgroup$
    – Johan Löfberg
    13 hours ago










  • $begingroup$
    @JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
    $endgroup$
    – Chandan Pradhan
    12 hours ago






  • 1




    $begingroup$
    Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
    $endgroup$
    – Johan Löfberg
    6 hours ago















0












$begingroup$


I have the following constraint for the optimization problem in hand:



$$fracb_klog_2 left(1 + fracp_k alpha_ksum_j neq k p_j alpha_j + sum_n sum_l Xi_n,l,k 2^-2 v_n,l right) + 2 fracsum_n sum_l v_n,l C_F leq epsilon$$



where the variables are $v_n,l$, $p_k$, $p_j, ; j neq k$. The constants are $alpha_k$, $alpha_j$, $b_k$, $C_F$, $Xi_n,l,k$.



The constraint is non-convex in $v_n,l, p_k, p_j, ; j neq k$. I am looking solve the problem with sucessive convex approximation approach.



I need some suggestion on feasibilty of the problem in terms of it if its possible to have a convex approximation for the above constraint and or suggest some method to solve it.










share|cite|improve this question











$endgroup$







  • 1




    $begingroup$
    The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
    $endgroup$
    – Rodrigo de Azevedo
    15 hours ago






  • 2




    $begingroup$
    Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
    $endgroup$
    – Johan Löfberg
    13 hours ago










  • $begingroup$
    @JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
    $endgroup$
    – Chandan Pradhan
    12 hours ago






  • 1




    $begingroup$
    Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
    $endgroup$
    – Johan Löfberg
    6 hours ago













0












0








0





$begingroup$


I have the following constraint for the optimization problem in hand:



$$fracb_klog_2 left(1 + fracp_k alpha_ksum_j neq k p_j alpha_j + sum_n sum_l Xi_n,l,k 2^-2 v_n,l right) + 2 fracsum_n sum_l v_n,l C_F leq epsilon$$



where the variables are $v_n,l$, $p_k$, $p_j, ; j neq k$. The constants are $alpha_k$, $alpha_j$, $b_k$, $C_F$, $Xi_n,l,k$.



The constraint is non-convex in $v_n,l, p_k, p_j, ; j neq k$. I am looking solve the problem with sucessive convex approximation approach.



I need some suggestion on feasibilty of the problem in terms of it if its possible to have a convex approximation for the above constraint and or suggest some method to solve it.










share|cite|improve this question











$endgroup$




I have the following constraint for the optimization problem in hand:



$$fracb_klog_2 left(1 + fracp_k alpha_ksum_j neq k p_j alpha_j + sum_n sum_l Xi_n,l,k 2^-2 v_n,l right) + 2 fracsum_n sum_l v_n,l C_F leq epsilon$$



where the variables are $v_n,l$, $p_k$, $p_j, ; j neq k$. The constants are $alpha_k$, $alpha_j$, $b_k$, $C_F$, $Xi_n,l,k$.



The constraint is non-convex in $v_n,l, p_k, p_j, ; j neq k$. I am looking solve the problem with sucessive convex approximation approach.



I need some suggestion on feasibilty of the problem in terms of it if its possible to have a convex approximation for the above constraint and or suggest some method to solve it.







optimization nonlinear-optimization non-convex-optimization






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited 1 hour ago









Javi

3,0212832




3,0212832










asked 16 hours ago









Chandan PradhanChandan Pradhan

353




353







  • 1




    $begingroup$
    The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
    $endgroup$
    – Rodrigo de Azevedo
    15 hours ago






  • 2




    $begingroup$
    Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
    $endgroup$
    – Johan Löfberg
    13 hours ago










  • $begingroup$
    @JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
    $endgroup$
    – Chandan Pradhan
    12 hours ago






  • 1




    $begingroup$
    Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
    $endgroup$
    – Johan Löfberg
    6 hours ago












  • 1




    $begingroup$
    The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
    $endgroup$
    – Rodrigo de Azevedo
    15 hours ago






  • 2




    $begingroup$
    Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
    $endgroup$
    – Johan Löfberg
    13 hours ago










  • $begingroup$
    @JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
    $endgroup$
    – Chandan Pradhan
    12 hours ago






  • 1




    $begingroup$
    Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
    $endgroup$
    – Johan Löfberg
    6 hours ago







1




1




$begingroup$
The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
$endgroup$
– Rodrigo de Azevedo
15 hours ago




$begingroup$
The Optimization Ocean is full of hopelessness, with a few archipelagos of tiny atolls (e.g., LP, QP, SDP, etc) where life is easy.
$endgroup$
– Rodrigo de Azevedo
15 hours ago




2




2




$begingroup$
Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
$endgroup$
– Johan Löfberg
13 hours ago




$begingroup$
Any particular reason for manually deriving convex approximations and then using an iterative approach, instead of simply using a general purpose nonlinear solver which effectively does this for you, but with added general tricks and knowledge to handle nonlinear programs.
$endgroup$
– Johan Löfberg
13 hours ago












$begingroup$
@JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
$endgroup$
– Chandan Pradhan
12 hours ago




$begingroup$
@JohanLöfberg My idea was to solve the problem with respect to both $v_n,l$ and $p_k$ and formulate and SCA problem. I am not sure if it can be solved using non-linear solvers. I dont have experience with nonlinear solver and that's why I am not sure feasibility of the problem.
$endgroup$
– Chandan Pradhan
12 hours ago




1




1




$begingroup$
Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
$endgroup$
– Johan Löfberg
6 hours ago




$begingroup$
Nonlinear solvers solve, well, nonlinear problems. Your problem is nonlinear. Most often when people start messing abour with homemade sequential convex approximations etc, they are simply reinventing the wheel, or bad approximations of a very standard wheel. Start with a standard nonlinear solver and see where it gets you. If that isn't good enough, try developing your own heuristics.
$endgroup$
– Johan Löfberg
6 hours ago










0






active

oldest

votes











Your Answer





StackExchange.ifUsing("editor", function ()
return StackExchange.using("mathjaxEditing", function ()
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix)
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
);
);
, "mathjax-editing");

StackExchange.ready(function()
var channelOptions =
tags: "".split(" "),
id: "69"
;
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
,
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
);



);













draft saved

draft discarded


















StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3164168%2fconvex-approximation-of-the-non-convex-function%23new-answer', 'question_page');

);

Post as a guest















Required, but never shown

























0






active

oldest

votes








0






active

oldest

votes









active

oldest

votes






active

oldest

votes















draft saved

draft discarded
















































Thanks for contributing an answer to Mathematics Stack Exchange!


  • 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.

Use MathJax to format equations. MathJax reference.


To learn more, see our tips on writing great answers.




draft saved


draft discarded














StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3164168%2fconvex-approximation-of-the-non-convex-function%23new-answer', 'question_page');

);

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







Popular posts from this blog

Triangular numbers and gcdProving sum of a set is $0 pmod n$ if $n$ is odd, or $fracn2 pmod n$ if $n$ is even?Is greatest common divisor of two numbers really their smallest linear combination?GCD, LCM RelationshipProve a set of nonnegative integers with greatest common divisor 1 and closed under addition has all but finite many nonnegative integers.all pairs of a and b in an equation containing gcdTriangular Numbers Modulo $k$ - Hit All Values?Understanding the Existence and Uniqueness of the GCDGCD and LCM with logical symbolsThe greatest common divisor of two positive integers less than 100 is equal to 3. Their least common multiple is twelve times one of the integers.Suppose that for all integers $x$, $x|a$ and $x|b$ if and only if $x|c$. Then $c = gcd(a,b)$Which is the gcd of 2 numbers which are multiplied and the result is 600000?

Ingelân Ynhâld Etymology | Geografy | Skiednis | Polityk en bestjoer | Ekonomy | Demografy | Kultuer | Klimaat | Sjoch ek | Keppelings om utens | Boarnen, noaten en referinsjes Navigaasjemenuwww.gov.ukOffisjele webside fan it regear fan it Feriene KeninkrykOffisjele webside fan it Britske FerkearsburoNederlânsktalige ynformaasje fan it Britske FerkearsburoOffisjele webside fan English Heritage, de organisaasje dy't him ynset foar it behâld fan it Ingelske kultuergoedYnwennertallen fan alle Britske stêden út 'e folkstelling fan 2011Notes en References, op dizze sideEngland

Հադիս Բովանդակություն Անվանում և նշանակություն | Դասակարգում | Աղբյուրներ | Նավարկման ցանկ