[R] 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]]
> 
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