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== | '''Interior point methods''' (also referred to as '''barrier methods''') are a certain class of [[algorithm]]s to solve linear and nonlinear [[convex optimization]] problems. | ||
[[File:karmarkar.png|thumb|200px|right|Example solution]] | |||
The interior point method was invented by [[John von Neumann]].<ref>{{Cite book|first1=George B.|last1= Dantzig |first2= Mukund N. |last2=Thapa|year= 2003|title= Linear Programming 2: Theory and Extensions|publisher=Springer-Verlag}}</ref> Von Neumann suggested a new method of linear programming, using the homogeneous linear system of Gordan (1873) which was later popularized by [[Karmarkar's algorithm]], developed by [[Narendra Karmarkar]] in 1984 for [[linear programming]]. The method consists of a [[self-concordant]] [[barrier function]] used to encode the [[convex set]]. Contrary to the [[Simplex algorithm|simplex method]], it reaches an optimal solution by traversing the interior of the [[feasible region]]. | |||
Any convex optimization problem can be transformed into minimizing (or maximizing) a [[linear function]] over a convex set by converting to the [[epigraph form]].<ref>{{cite book|last=Boyd|first=Stephen|last2=Vandenberghe|first2=Lieven|title=Convex Optimization|publisher=[[Cambridge University Press]]|location=Cambridge |year=2004|pages=143|isbn=0-521-83378-7|mr=2061575}}</ref> The idea of encoding the [[candidate solution|feasible set]] using a barrier and designing barrier methods was studied in the early 1960s by, amongst others, Anthony V. Fiacco and Garth P. McCormick. These ideas were mainly developed for general [[nonlinear programming]], but they were later abandoned due to the presence of more competitive methods for this class of problems (e.g. [[sequential quadratic programming]]). | |||
== | [[Yurii Nesterov]] and [[Arkadi Nemirovski]] came up with a special class of such barriers that can be used to encode any convex set. They guarantee that the number of [[iteration]]s of the algorithm is bounded by a polynomial in the dimension and accuracy of the solution.<ref>{{Cite journal|mr=2115066|doi=10.1090/S0273-0979-04-01040-7|title=The interior-point revolution in optimization: History, recent developments, and lasting consequences|year=2004|last1=Wright|first1=Margaret H.|journal=Bulletin of the American Mathematical Society|volume=42|pages=39 }}</ref> | ||
Karmarkar's breakthrough revitalized the study of interior point methods and barrier problems, showing that it was possible to create an algorithm for linear programming characterized by [[polynomial time|polynomial complexity]] and, moreover, that was competitive with the simplex method. | |||
Already [[Leonid Khachiyan|Khachiyan]]'s [[ellipsoid method]] was a polynomial time algorithm; however, in practice it was too slow to be of practical interest. | |||
= | The class of primal-dual path-following interior point methods is considered the most successful. | ||
[[Mehrotra predictor-corrector method|Mehrotra's predictor-corrector algorithm]] provides the basis for most implementations of this class of methods{{Citation needed|date=February 2011}}. | |||
==Primal-dual interior point method for nonlinear optimization== | |||
The primal-dual method's idea is easy to demonstrate for constrained [[nonlinear optimization]]. | |||
For simplicity consider the all-inequality version of a nonlinear optimization problem: | |||
:minimize <math>f(x)</math> subject to <math>c(x) \ge 0~~ x \in \mathbb{R}^n, c(x) \in \mathbb{R}^m~~~~~~(1)</math>. | |||
The logarithmic [[barrier function]] associated with (1) is | |||
:<math>B(x,\mu) = f(x) - \mu~ \sum_{i=1}^m\ln(c_i(x))~~~~~(2)</math> | |||
Here <math>\mu</math> is a small positive scalar, sometimes called the "barrier parameter". As <math>\mu</math> converges to zero the minimum of <math>B(x,\mu)</math> should converge to a solution of (1). | |||
The barrier function [[gradient]] is | |||
:<math>g_b = g - \mu\sum_{i=1}^m \frac{1}{c_i(x)} \nabla c_i(x)~~~~~~(3)</math> | |||
where <math>g</math> is the gradient of the original function <math>f(x)</math> and <math>\nabla c_i</math> is the gradient of <math>c_i</math>. | |||
In addition to the original ("primal") variable <math>x</math> we introduce a [[Lagrange multiplier]] inspired [[Lagrange_multiplier#The_strong_Lagrangian_principle:_Lagrange_duality|dual]] variable <math>\lambda\in \mathbb{R} ^m</math>(sometimes called "slack variable") | |||
:<math>\forall_{i=1}^m c_i(x) \lambda_i=\mu~~~~~~~(4)</math> | |||
(4) is sometimes called the "perturbed complementarity" condition, for its resemblance to "complementary slackness" in [[KKT conditions]]. | |||
We try to find those <math>(x_\mu, \lambda_\mu)</math> for which the gradient of the barrier function is zero. | |||
Applying (4) to (3) we get equation for gradient: | |||
:<math>g - A^T \lambda = 0~~~~~~(5)</math> | |||
where the matrix <math>A</math> is the constraint <math>c(x)</math> [[Jacobian matrix and determinant|Jacobian]]. | |||
The intuition behind (5) is that the gradient of <math>f(x)</math> should lie in the subspace spanned by the constraints' gradients. The "perturbed complementarity" with small <math>\mu</math> (4) can be understood as the condition that the solution should either lie near the boundary <math>c_i(x) = 0</math> or that the projection of the gradient <math>g</math> on the constraint component <math>c_i(x)</math> normal should be almost zero. | |||
Applying [[Newton method|Newton's method]] to (4) and (5) we get an equation for <math>(x, \lambda)</math> update <math>(p_x, p_\lambda)</math>: | |||
:<math>\begin{pmatrix} | |||
W & -A^T \\ | |||
\Lambda A & C | |||
\end{pmatrix}\begin{pmatrix} | |||
p_x \\ | |||
p_\lambda | |||
\end{pmatrix}=\begin{pmatrix} | |||
-g + A^T \lambda \\ | |||
\mu 1 - C \lambda | |||
\end{pmatrix}</math> | |||
where <math>W</math> is the [[Hessian matrix]] of <math>f(x)</math> and <math>\Lambda</math> is a [[diagonal matrix]] of <math>\lambda</math>. | |||
Because of (1), (4) the condition | |||
:<math>\lambda \ge 0</math> | |||
should be enforced at each step. This can be done by choosing appropriate <math>\alpha</math>: | |||
:<math>(x,\lambda) \rightarrow (x+ \alpha p_x, \lambda + \alpha p_\lambda)</math>. | |||
==See also== | |||
*[[Augmented Lagrangian method]] | |||
*[[Penalty method]] | |||
*[[Karush–Kuhn–Tucker conditions]] | |||
==References== | |||
{{Reflist}} | |||
== Bibliography == | |||
* {{cite book|last1=Bonnans|first1=J. Frédéric|last2=Gilbert|first2=J. Charles|last3=Lemaréchal|first3=Claude| authorlink3=Claude Lemaréchal|last4=Sagastizábal|first4=Claudia A.|title=Numerical optimization: Theoretical and practical aspects|url=http://www.springer.com/mathematics/applications/book/978-3-540-35445-1|edition=Second revised ed. of translation of 1997 <!-- ''Optimisation numérique: Aspects théoriques et pratiques'' --> French| series=Universitext|publisher=Springer-Verlag|location=Berlin|year=2006|pages=xiv+490|isbn=3-540-35445-X|doi=10.1007/978-3-540-35447-5|mr=2265882}} | |||
* {{cite journal|doi=10.1145/800057.808695|url=http://retis.sssup.it/~bini/teaching/optim2010/karmarkar.pdf|chapter=A new polynomial-time algorithm for linear programming|title=Proceedings of the sixteenth annual ACM symposium on Theory of computing - STOC '84|year=1984|last1=Karmarkar|first1=N.|isbn=0-89791-133-4|pages=302}} | |||
* {{Cite journal|doi=10.1137/0802028|title=On the Implementation of a Primal-Dual Interior Point Method|year=1992|last1=Mehrotra|first1=Sanjay|journal=SIAM Journal on Optimization|volume=2|issue=4|pages=575}} | |||
*{{cite book|title = Numerical Optimization | first=Jorge| last = Nocedal | coauthors= and Stephen Wright| year=1999 | publisher=Springer | location=New York, NY| isbn=0-387-98793-2}} | |||
*{{Cite book | last1=Press | first1=WH | last2=Teukolsky | first2=SA | last3=Vetterling | first3=WT | last4=Flannery | first4=BP | year=2007 | title=Numerical Recipes: The Art of Scientific Computing | edition=3rd | publisher=Cambridge University Press | publication-place=New York | isbn=978-0-521-88068-8 | chapter=Section 10.11. Linear Programming: Interior-Point Methods | chapter-url=http://apps.nrbook.com/empanel/index.html#pg=537}} | |||
*{{cite book|title = Primal-Dual Interior-Point Methods | first=Stephen| last = Wright | year=1997 | publisher=SIAM | location=Philadelphia, PA| isbn=0-89871-382-X}} | |||
*{{cite book|title = Convex Optimization |last1=Boyd|first1=Stephen|last2=Vandenberghe|first2=Lieven|year=2004|publisher=Cambridge University Press|url=http://www.stanford.edu/~boyd/cvxbook/}} | |||
{{Use dmy dates|date=February 2011}} | |||
{{Optimization algorithms|convex}} | |||
[[Category:Optimization algorithms and methods]] |
Revision as of 22:39, 31 January 2014
Interior point methods (also referred to as barrier methods) are a certain class of algorithms to solve linear and nonlinear convex optimization problems.
The interior point method was invented by John von Neumann.[1] Von Neumann suggested a new method of linear programming, using the homogeneous linear system of Gordan (1873) which was later popularized by Karmarkar's algorithm, developed by Narendra Karmarkar in 1984 for linear programming. The method consists of a self-concordant barrier function used to encode the convex set. Contrary to the simplex method, it reaches an optimal solution by traversing the interior of the feasible region.
Any convex optimization problem can be transformed into minimizing (or maximizing) a linear function over a convex set by converting to the epigraph form.[2] The idea of encoding the feasible set using a barrier and designing barrier methods was studied in the early 1960s by, amongst others, Anthony V. Fiacco and Garth P. McCormick. These ideas were mainly developed for general nonlinear programming, but they were later abandoned due to the presence of more competitive methods for this class of problems (e.g. sequential quadratic programming).
Yurii Nesterov and Arkadi Nemirovski came up with a special class of such barriers that can be used to encode any convex set. They guarantee that the number of iterations of the algorithm is bounded by a polynomial in the dimension and accuracy of the solution.[3]
Karmarkar's breakthrough revitalized the study of interior point methods and barrier problems, showing that it was possible to create an algorithm for linear programming characterized by polynomial complexity and, moreover, that was competitive with the simplex method. Already Khachiyan's ellipsoid method was a polynomial time algorithm; however, in practice it was too slow to be of practical interest.
The class of primal-dual path-following interior point methods is considered the most successful. Mehrotra's predictor-corrector algorithm provides the basis for most implementations of this class of methodsPotter or Ceramic Artist Truman Bedell from Rexton, has interests which include ceramics, best property developers in singapore developers in singapore and scrabble. Was especially enthused after visiting Alejandro de Humboldt National Park..
Primal-dual interior point method for nonlinear optimization
The primal-dual method's idea is easy to demonstrate for constrained nonlinear optimization. For simplicity consider the all-inequality version of a nonlinear optimization problem:
The logarithmic barrier function associated with (1) is
Here is a small positive scalar, sometimes called the "barrier parameter". As converges to zero the minimum of should converge to a solution of (1).
The barrier function gradient is
where is the gradient of the original function and is the gradient of .
In addition to the original ("primal") variable we introduce a Lagrange multiplier inspired dual variable (sometimes called "slack variable")
(4) is sometimes called the "perturbed complementarity" condition, for its resemblance to "complementary slackness" in KKT conditions.
We try to find those for which the gradient of the barrier function is zero.
Applying (4) to (3) we get equation for gradient:
where the matrix is the constraint Jacobian.
The intuition behind (5) is that the gradient of should lie in the subspace spanned by the constraints' gradients. The "perturbed complementarity" with small (4) can be understood as the condition that the solution should either lie near the boundary or that the projection of the gradient on the constraint component normal should be almost zero.
Applying Newton's method to (4) and (5) we get an equation for update :
where is the Hessian matrix of and is a diagonal matrix of .
Because of (1), (4) the condition
should be enforced at each step. This can be done by choosing appropriate :
See also
References
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Bibliography
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Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules
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A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running
The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more
There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang - One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting
In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang
Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules
Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.
A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running
The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more
There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
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Template:Optimization algorithms
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My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - ↑ 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - ↑ One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting
In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang
Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules
Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.
A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running
The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more
There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang