Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

classic Classic list List threaded Threaded
5 messages Options
Reply | Threaded
Open this post in threaded view
|

Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

Keshava PRASADa Halemane
Friends:
i am a retired Professor -
not having any access to the resources (human/financial/business/whatever)
that may be required -
therefore i am seeking implementation of my algorithm 'spdspds' -
a novel algorithm for solving Linear Programming Problems with O(L^1.5)
computational complexity -
in order to show/convince the esteemed world optimization community
that it is indeed a great grand breakthrough in terms of achievement of the
linear programming performance challenge of the millennium -
with far reaching deep impact on optimization algorithm development in
general -
holy grail fantasy realized!

I need some individual or team who is interested & willing to work on this.
Earlier experience in implementation of optimization/LP algorithms will
greatly help.

You may access / download / read my paper -
"Unbelievable *O*(*L*^1.5) worst case computational complexity achieved by
spdspds algorithm for linear programming problem"
which is available at - arxiv . org / abs / 1405 . 6902

Thanks a lot.
 - Dr(Prof) Keshava Prasad Halemane

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

J C Nash
Your best chance to get some interest is to adapt an existing package
such as linprog or lpSolve to use your algorithm. Then there will be
sufficient structure to allow R users and developers to see your
ideas working, even if they are not efficiently programmed. It's
always easier to start with something that is working and improve it.
And you would be able to show comparisons of the existing examples by
the current and new methods.

I've worked on a lot of optimization (mainly function minimization) methods
over many decades, and there are several "brilliant" ideas that have not
turned out to be very good practical methods, while some rather pedestrian
ideas have proved reliable and effective, even if they don't fulfill nice
theoretical properties. There are, however, a few nice cases where theory
and practice are both great.

JN

On 2020-06-10 12:36 a.m., Keshava PRASADa Halemane wrote:

> Friends:
> i am a retired Professor -
> not having any access to the resources (human/financial/business/whatever)
> that may be required -
> therefore i am seeking implementation of my algorithm 'spdspds' -
> a novel algorithm for solving Linear Programming Problems with O(L^1.5)
> computational complexity -
> in order to show/convince the esteemed world optimization community
> that it is indeed a great grand breakthrough in terms of achievement of the
> linear programming performance challenge of the millennium -
> with far reaching deep impact on optimization algorithm development in
> general -
> holy grail fantasy realized!
>
> I need some individual or team who is interested & willing to work on this.
> Earlier experience in implementation of optimization/LP algorithms will
> greatly help.
>
> You may access / download / read my paper -
> "Unbelievable *O*(*L*^1.5) worst case computational complexity achieved by
> spdspds algorithm for linear programming problem"
> which is available at - arxiv . org / abs / 1405 . 6902
>
> Thanks a lot.
>  - Dr(Prof) Keshava Prasad Halemane
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

Chris Evans


----- Original Message -----
> From: "J C Nash" <[hidden email]>
> To: "Keshava PRASADa Halemane" <[hidden email]>, [hidden email]
> Sent: Thursday, 11 June, 2020 01:00:29
> Subject: Re: [R] Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming
> Problems with O(L^1.5) computational complexity

[snipped]
 
> I've worked on a lot of optimization (mainly function minimization) methods
> over many decades, and there are several "brilliant" ideas that have not
> turned out to be very good practical methods, while some rather pedestrian
> ideas have proved reliable and effective, even if they don't fulfill nice
> theoretical properties. There are, however, a few nice cases where theory
> and practice are both great.

Fortune nomination!   Glorious.  Thanks for making me smile.

Chris

[rest snipped]

--
Small contribution in our coronavirus rigours:
https://www.coresystemtrust.org.uk/home/free-options-to-replace-paper-core-forms-during-the-coronavirus-pandemic/

Chris Evans <[hidden email]> Visiting Professor, University of Sheffield <[hidden email]>
I do some consultation work for the University of Roehampton <[hidden email]> and other places
but <[hidden email]> remains my main Email address.  I have a work web site at:
   https://www.psyctc.org/psyctc/
and a site I manage for CORE and CORE system trust at:
   http://www.coresystemtrust.org.uk/
I have "semigrated" to France, see:
   https://www.psyctc.org/pelerinage2016/semigrating-to-france/ 
   https://www.psyctc.org/pelerinage2016/register-to-get-updates-from-pelerinage2016/

If you want an Emeeting, I am trying to keep them to Thursdays and my diary is at:
   https://www.psyctc.org/pelerinage2016/ceworkdiary/
Beware: French time, generally an hour ahead of UK.

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

jacob bogers
In reply to this post by Keshava PRASADa Halemane
" not having any access to the resources "
You have internet (as is proven by sending this email)
you even have R cli these days on mobile (I do anyway).
Learn R , code,  let me know how it turns out



On Wed, Jun 10, 2020 at 8:46 PM Keshava PRASADa Halemane <
[hidden email]> wrote:

> Friends:
> i am a retired Professor -
> not having any access to the resources (human/financial/business/whatever)
> that may be required -
> therefore i am seeking implementation of my algorithm 'spdspds' -
> a novel algorithm for solving Linear Programming Problems with O(L^1.5)
> computational complexity -
> in order to show/convince the esteemed world optimization community
> that it is indeed a great grand breakthrough in terms of achievement of the
> linear programming performance challenge of the millennium -
> with far reaching deep impact on optimization algorithm development in
> general -
> holy grail fantasy realized!
>
> I need some individual or team who is interested & willing to work on this.
> Earlier experience in implementation of optimization/LP algorithms will
> greatly help.
>
> You may access / download / read my paper -
> "Unbelievable *O*(*L*^1.5) worst case computational complexity achieved by
> spdspds algorithm for linear programming problem"
> which is available at - arxiv . org / abs / 1405 . 6902
>
> Thanks a lot.
>  - Dr(Prof) Keshava Prasad Halemane
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Seeking implementation of my algorithm 'spdspds' - a novel algorithm for solving Linear Programming Problems with O(L^1.5) computational complexity

Abby Spurdle
In reply to this post by Keshava PRASADa Halemane
> solving Linear Programming Problems with O(L^1.5)
> computational complexity

I'm not an expert on this topic.
However, a quick glance at the topic suggests that these sorts of
algorithms are usually exponential in "n", here the number of
variables/dimensions.
Apparently, "L" is the number of input bits.

Your notation suggests your algorithm is dependent on the number input
bits only, and is otherwise constant in the number of
variables/dimensions.
So, we can solve an LP with hundreds of millions of variables,
near-instantaneously...?

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.