carlostoro.com Report : Visit Site


  • Server:Apache/2.4.10 (Ubunt...

    The main IP address: 94.76.213.109,Your server United Kingdom,Maidenhead ISP:Simply Transit Ltd  TLD:com CountryCode:GB

    The description :the simplex algorithm seeks a solution between feasible region extreme points in linear programming problems which satisfies the optimality criterion. simplex algorithm is based in an operation called...

    This report updates in 05-Sep-2018

Created Date:2011-09-11
Changed Date:2016-08-22

Technical data of the carlostoro.com


Geo IP provides you such as latitude, longitude and ISP (Internet Service Provider) etc. informations. Our GeoIP service found where is host carlostoro.com. Currently, hosted in United Kingdom and its service provider is Simply Transit Ltd .

Latitude: 51.522789001465
Longitude: -0.71986001729965
Country: United Kingdom (GB)
City: Maidenhead
Region: England
ISP: Simply Transit Ltd
    mathstools.com 

HTTP Header Analysis


HTTP Header information is a part of HTTP protocol that a user's browser sends to called Apache/2.4.10 (Ubuntu) containing the details of what the browser wants and will accept back from the web server.

Content-Length:15488
Content-Encoding:gzip
Set-Cookie:symfony=89832ld8ttgmn5epef02irjpj2; path=/
Vary:Accept-Encoding
Keep-Alive:timeout=5, max=100
Server:Apache/2.4.10 (Ubuntu)
Connection:Keep-Alive
Date:Wed, 05 Sep 2018 06:29:55 GMT
Content-Type:text/html; charset=utf-8

DNS

soa:nsv1.plaindns.net. root.dns1.nominalia.com. 1515161588 86400 7200 2592000 300
ns:nsv1.plaindns.net.
nsv2.plaindns.net.
ipv4:IP:94.76.213.109
ASN:29550
OWNER:SIMPLYTRANSIT, GB
Country:GB

HtmlToText

-- -- -- -- -- loading data ... please wait ... -- -- mathstools apps apps. directory 3d-functions plotter runge kutta methods the simplex algorithm eigenvalues calculator 2d-functions plotter functions analyzer fourier series prime numbers calculator mathstools applet latex editor theory linear programming the simplex algorithm linear programming simplex pivot element the 2-phase method duality the online simplex method numerical methods differential equations runge-kutta methods fehlberg methods runge-kutta on line calculus derivates chain rule complex analysis the complex plane complex variable functions the complex derivate complex integration cauchy's integral formula special relativity maxwell's equations lorentz minkowski e=mc2 fourier analysis fourier series hilbert spaces fourier series convergence discontinuities behavour the online fourier series non linear programming linear programing basics differentiable functions convex functions on line optimizations lagrange multipliers linear algebra eigenvalues matrix diagonalizations jordan canonical form online systems differential geometry manifolds tensorial algebra geodesics lagrangian method examples linear programming the 2-phase method simplex method example finite solution example unbounded solution sample infinite solutions sample uncompatible constraints numerical analysis the euler's method three eighths rule in matlab dormand/prince 4 and 5 modelling the brusselator linear algebra jordan cannonical form 3x3 jordan 3x3(2) maths mobile android mathstools 3d-functions plotter android simplex android calculator runge-kutta methods android integrator matrix studio contact contact us mathstools publishing theory linear programming the simplex algorithm linear programming simplex pivot element the 2-phase method duality the online simplex method numerical methods differential equations runge-kutta methods fehlberg methods runge-kutta on line calculus derivates chain rule complex analysis the complex plane complex variable functions the complex derivate complex integration cauchy's integral formula special relativity maxwell's equations lorentz minkowski e=mc2 fourier analysis fourier series hilbert spaces fourier series convergence discontinuities behavour the online fourier series non linear programming linear programing basics differentiable functions convex functions on line optimizations lagrange multipliers linear algebra eigenvalues matrix diagonalizations jordan canonical form online systems differential geometry manifolds tensorial algebra geodesics lagrangian method apps. directory 3d-functions plotter runge kutta methods the simplex algorithm eigenvalues calculator 2d-functions plotter functions analyzer fourier series prime numbers calculator mathstools applet latex editor maths mobile android mathstools 3d-functions plotter android simplex android calculator runge-kutta methods android integrator matrix studio examples linear programming the 2-phase method simplex method example finite solution example unbounded solution sample infinite solutions sample uncompatible constraints numerical analysis the euler's method three eighths rule in matlab dormand/prince 4 and 5 modelling the brusselator linear algebra jordan cannonical form 3x3 jordan 3x3(2) contact us contact us dictionary definitions the simplex algorithm basic concepts and principles the simplex algorithm performs iterations into the extreme points set of feasible region, checking for each one if optimalit criterion holds. the simplex algorithm whose invention is due to george dantzig in 1947 and in 1975 earned him the national medal of science is the main method for solving linear programming problems. given a linnear programming standard problem p, minimize c t x subject to ax = b x ≥ 0 where a∈ m mxn , rk(a)=m, b∈r m , c∈r n , and n≥m. thus, m is the number of constraits (files of matrix a or dimension of vector b) and n is the number of variables (columns of matriz a or dimension of vector c). if p has optimal solution x k finite, we know from linear programming theory that x k is contained into the extreme points subset of feasible points set, s. simplex algorithm basic idea is to perform iterations into extreme points set until a condition called "optimality criterion" holds. if it holds at a certain extreme point x k , then this x k is the solution that we are looking for. extended theory suppose that x, extreme point of s. because the extreme points set is formed by solutions of ax=b subsystems, x can be write as x = [b -1 b, 0] t , with b mxm-square a submatrix with rank m. we can decompose a in b and n submatrices, b as said, is submatrix with rank m and n is the matrix formed with the remaining columns from a.(remember that n≥m). lets w another point from the feasible region s. then aw = b, ie bw b + nw n = b because b is invertible w b = b -1 b - b -1 nw n applying c t to w we obtain c t w = c b t w b + c n t w n = c b t (b -1 b - b -1 nw n ) + c n t w n (*) as w belongs to feasible region, we know that w n ≥ 0, so, if x were the optimal solution, then it must holds c t w > c t x = c t b -1 b now, we substitute at (*), obtain c n t - c b t b -1 n > 0 (1) this is the basic idea from the simplex algorithm that we were refering before, and it is call optimality criterion the simplex algorithm optimality criterion c n t - c b t b -1 n > 0 if this condition holds, then x is the optimal solution of p. the criterion equation has as coordinates c j - c b t b -1 a j = c j - c b t y j = c j - z j being a j , column vector of n. in resume, optimality criterion is z j - c j < 0, con z j = c b t b -1 a j suposse now than (1) does not holds, ie c n t - c b t b -1 n ≥ 0 (2) them there are two possibilities ... 1) y j = b -1 a j ≤ 0 ∀j, then we can build x = w + λ d j , being d j = (-b -1 a j , e j ) t we know that d j is an extreme direction of feasible set s, in particular ad j = 0 so x = w + λ d j is also feasible solution ∀ λ ≥ 0. in another way c t x = c t w + λd j = c t w + λ(-c t b -1 a j ) d j = c t w - λ(z j - c j ) → -∞ when λ → ∞ this means that we can make the solution as small as want without leaving the feasible set s and so this is a unbounded case solution 2) the vector y j = b -1 a j has someone positive component them is possible to build other feasible solution (it will be into the extreme point of s) where the function is smaller the new solutions is build as follows x = w + λd j being d j = (-b -1 a j e j ) t and λ = min{β/y ij : y ij > 0}, β = b -1 b. with this value λ, x is feasible solution and if for example λ = β j / y ij then x is the basic solution associed to the matrix b , = (a 1 , a 2 , ..., a r-1 , a j , a r+1 , ..., , a m ) ie, that is, we changed a vector by another (we have substituted the vector in r position for which is in place j). in resume we have built a solution from other. note: if there are various indexes satisfying z j - c j > 0 then the operations is performed on the index k that satisfies z j - c k = max (z j - c j ), con z j - c j > 0 overview of the simplex method the extreme points x 0 , ..., x s , are the solutions for the systms bx=b, with b mxm submatrix of initial matrix a. the optimal solution, if there, should be between these points... given an extreme point x i in the feasible set, we check if the optimality criterion holds for it, if does then x i is the optimal solution founded. otherwise, one of these two situations can happen: 1) unbouded solution. 2) it is possible to iterate to next extreme point and test the optimality criterion for it. this is the simplex algorithm basic idea, iterating between the extreme points of feasible set, which are solutions of linear systems equations taken from square submatrices of constraints matrix a, and make this until one of them meets the optimality criterion. there remains the problem of obtaining these solutions, we will see in section simplex calculations how simplex algorithm offers us a calculation

URL analysis for carlostoro.com


http://www.mathstools.com/section/main/jordan_form_example_3x3
http://www.mathstools.com/section/main/jordan_form_3x3_triple_root
http://www.mathstools.com/section/main/derivate_under_integral
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http://www.mathstools.com/section/main/on_line_fourier_series
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Whois Information


Whois is a protocol that is access to registering information. You can reach when the website was registered, when it will be expire, what is contact details of the site with the following informations. In a nutshell, it includes these informations;

Domain Name: CARLOSTORO.COM
Registry Domain ID: 1676569940_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.networksolutions.com
Registrar URL: http://networksolutions.com
Updated Date: 2016-08-22T04:01:50Z
Creation Date: 2011-09-11T22:12:20Z
Registry Expiry Date: 2018-09-11T22:12:20Z
Registrar: Network Solutions, LLC.
Registrar IANA ID: 2
Registrar Abuse Contact Email: [email protected]
Registrar Abuse Contact Phone: +1.8003337680
Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Name Server: NSV1.PLAINDNS.NET
Name Server: NSV2.PLAINDNS.NET
DNSSEC: unsigned
URL of the ICANN Whois Inaccuracy Complaint Form: https://www.icann.org/wicf/
>>> Last update of whois database: 2017-09-09T06:21:03Z <<<

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The Registry database contains ONLY .COM, .NET, .EDU domains and
Registrars.

  REGISTRAR Network Solutions, LLC.

SERVERS

  SERVER com.whois-servers.net

  ARGS domain =carlostoro.com

  PORT 43

  TYPE domain

DOMAIN

  NAME carlostoro.com

  CHANGED 2016-08-22

  CREATED 2011-09-11

STATUS
clientTransferProhibited https://icann.org/epp#clientTransferProhibited

NSERVER

  NSV1.PLAINDNS.NET 195.110.124.143

  NSV2.PLAINDNS.NET 81.88.63.48

  REGISTERED yes

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