J. Brinkhuis (Jan)
http://repub.eur.nl/ppl/982/
List of Publicationsenhttp://repub.eur.nl/eur_signature.png
http://repub.eur.nl/
RePub, Erasmus University RepositoryA simple approach to discrete-time infinite horizon problems
http://repub.eur.nl/pub/79542/
Fri, 04 Dec 2015 00:00:01 GMT<div>J. Brinkhuis</div>
In this note, we consider a type of discrete-time infinite horizon problem that has one ingredient only, a constraint correspondence. The value function of a policy has an intuitive mono- tonicity property; this is the essence of the four standard theorems on the functional equation (‘the Bellman equation’). Some insight is offered into the boundedness condition for the value function that occurs in the formulation of these results: it can be interpreted as accountability of the loss of value caused by a non-optimal policy or, alternatively, it can be interpreted as irrelevance of devia- tions, in the distant future, from the considered policy. Without the boundedness condition, there is a gap, which can be viewed as the persistent potential positive impact of deviations, in the distant future, from the considered policy. The general stationary discrete-time infinite horizon optimization problem considered in Stokey and Lucas (1989) can be mapped to this type of problems and so the results in the present paper can be applied to this general class of problems.On the uniform limit condition for discrete-time infinite horizon problems
http://repub.eur.nl/pub/79541/
Thu, 03 Dec 2015 00:00:01 GMT<div>J. Brinkhuis</div>
In this note, a simplified version of the four main results for discrete-time infinite horizon problems, theorems 4.2-4.5 from Stokey, Lucas and Prescott (1989) [SLP], is presented. A novel assumption on these problems is proposed—the uniform limit condition, which is formulated in terms of the data of the problem. It can be used for example before one has started to look for the optimal value function and for an optimal plan or if one cannot find them analytically: one verifies the uniform limit condition and then one disposes of criteria for optimality of the value function and a plan in terms of the functional equation and the boundedness condition. A comparison to [SLP] is made. The version in [SLP] requires one to verify whether a candidate optimal value function satisfies the boundedness condition; it is easier to check the uniform limit condition instead, as is demonstrated by examples. There is essentially no loss of strength or generality compared to [SLP]. The necessary and sufficient conditions for optimality coincide in the present paper but not in [SLP]. The proofs in the present paper are shorter than in [SLP]. An earlier attempt to simplify, in Acemoglu (2009) --here the limit condition is used rather than the uniform limit condition-- is not correct.A new proof of the Lagrange multiplier rule
http://repub.eur.nl/pub/79540/
Wed, 02 Dec 2015 00:00:01 GMT<div>J. Brinkhuis</div><div>V. Protassov</div>
We present an elementary self-contained proof for the Lagrange multiplier rule. It does not refer to any substantial preparations and it is only based on the observation that a certain limit is positive. At the end of this note, the power of the Lagrange multiplier rule is analyzed.A method to measure enforcement effort in shipping
with incomplete information
http://repub.eur.nl/pub/77166/
Wed, 12 Nov 2014 00:00:01 GMT<div>X. Ji</div><div>J. Brinkhuis</div><div>S. Knapp</div>
__Abstract__
Current methods in the shipping industry to evaluate performance do not account for differences in fleet profiles of registries such as age, size or ship type and not for bad luck. This can lead to unfair evaluation of enforcement efforts of the international standards. Furthermore, incentives to improve performance are concentrated on decreasing detentions rather than incidents. This article proposes a new method to a longstanding problem to evaluate performance that rectifies shortcomings of the method currently used. The proposed method measures the enforcement effort by means of proxy variables and introduces incentives for improvement that go beyond the currently used ‘detention’. The aim is to provide a fair and transparent way. The proposed method is applied and results are compared with methods currently used to demonstrate how the rankings change. The method can be adapted to other areas of the shipping industry such as classification societies or ship management companies.Convex Duality and Calculus: Reduction to Cones
http://repub.eur.nl/pub/16362/
Sun, 01 Nov 2009 00:00:01 GMT<div>J. Brinkhuis</div>
An attempt is made to justify results from Convex Analysis by means of one method. Duality results, such as the Fenchel-Moreau theorem for convex functions, and formulas of convex calculus, such as the Moreau-Rockafellar formula for the subgradient of the sum of sublinear functions, are considered. All duality operators, all duality theorems, all standard binary operations, and all formulas of convex calculus are enumerated. The method consists of three automatic steps: first translation from the given setting to that of convex cones, then application of the standard operations and facts (the calculi) for convex cones, finally translation back to the original setting. The advantage is that the calculi are much simpler for convex cones than for other types of convex objects, such as convex sets, convex functions and sublinear functions. Exclusion of improper convex objects is not necessary, and recession directions are allowed as points of convex objects. The method can also be applied beyond the enumeration of the calculi.A linear programming proof of the second order conditions of nonlinear programming
http://repub.eur.nl/pub/13561/
Sun, 01 Feb 2009 00:00:01 GMT<div>J. Brinkhuis</div>
In this note we give a new, simple proof of the standard first and second order necessary conditions, under the Mangasarian–Fromovitz constraint qualification (MFCQ), for non-linear programming problems. We work under a mild constraint qualification, which is implied by MFCQ. This makes it possible to reduce the proof to the relatively easy case of inequality constraints only under MFCQ. This reduction makes use of relaxation of inequality constraints and it makes use of a penalty function. The new proof is based on the duality theorem for linear programming; the proofs in the literature are based on results of mathematical analysis. This paper completes the work in a recent note of Birbil et al. where a linear programming proof of the first order necessary conditions has been given, using relaxation of equality constraints.Implementation of a national database infrastructure for registration of clinical procedures and as tool for national benchmarking
http://repub.eur.nl/pub/52307/
Mon, 01 Dec 2008 00:00:01 GMT<div>E.T. van der Velde</div><div>J. Boorsma</div><div>M.J. Schalij</div><div>J. Brinkhuis</div><div>A. Kloosterman</div><div>N.H.J.J. van der Putten</div><div>W.A. Dijk</div><div>R. Hoekema</div><div>W.R.M. Dassen</div><div>R. Brand</div><div>I. van der Veen</div>
A D-induced duality and its applications
http://repub.eur.nl/pub/61693/
Tue, 01 Jul 2008 00:00:01 GMT<div>J. Brinkhuis</div><div>J. Zhang</div>
This paper attempts to extend the notion of duality for convex cones, by basing it on a prescribed conic ordering and a fixed bilinear mapping. This is an extension of the standard definition of dual cones, in the sense that the nonnegativity of the inner-product is replaced by a pre-specified conic ordering, defined by a convex cone D, and the inner-product itself is replaced by a general multi-dimensional bilinear mapping. This new type of duality is termed the D-induced duality in the paper. We further introduce the notion of D-induced polar sets within the same framework, which can be viewed as a generalization of the D-induced dual cones and is convenient to use for some practical applications. Properties of the extended duality, including the extended bi-polar theorem, are proven. Furthermore, attention is paid to the computation and approximation of the D-induced dual objects. We discuss, as examples, applications of the newly introduced D-induced duality concepts in robust conic optimization and the duality theory for multi-objective conic optimization.The Lagrange multiplier rule revisited
http://repub.eur.nl/pub/12016/
Thu, 03 Apr 2008 00:00:01 GMT<div>J. Brinkhuis</div><div>V. Protassov</div>
In this paper we give a short novel proof of the well-known Lagrange multiplier rule, discuss the sources of the power of this rule and consider several applications of this rule. The new proof does not use the implicit function theorem and combines the advantages of two of the most well-known proofs: it provides the useful geometric insight of the elimination approach based on differentiable curves and technically it is not more complicated than the simple penalty approach.
Then we emphasize that the power of the rule is the reversal of order of the natural tasks, elimination and differentiation. This turns the hardest task,
elimination, from a nonlinear problem into a linear one. This phenomenon is illustrated by several convincing examples of applications of the rule to various areas. Finally we give three hints on the use of the rule.Duality and calculi without exceptions for convex objects
http://repub.eur.nl/pub/11891/
Mon, 31 Mar 2008 00:00:01 GMT<div>J. Brinkhuis</div>
The aim of this paper is to make a contribution to the
investigation of the roots and essence of convex analysis, and to
the development of the duality formulas of convex calculus. This
is done by means of one single method: firstly conify, then
work with the calculus of convex cones, which consists of three
rules only, and finally deconify. This generates all
definitions of convex objects, duality operators, binary
operations and duality formulas, all without the usual need
to exclude degenerate situations. The duality operator for convex
function agrees with the usual one, the Legendre-Fenchel
transform, only for proper functions. It has the advantage over
the Legendre-Fenchel transform that the duality formula holds for
improper convex functions as well. This solves a well-known
problem, that has already been considered in Rockafellar's Convex
Analysis (R.T. Rockafellar, Convex Analysis, Princeton University Press, 1970). The value of this result is that it leads
to the general validity of the formulas of Convex Analysis that
depend on the duality formula for convex functions. The approach
leads to the systematic inclusion into convex sets of recession
directions, and a similar extension for convex functions. The
method to construct binary operations given in (ibidem) is
formalized, and this leads to some new duality formulas. An
existence result for extended solutions of arbitrary convex
optimization problems is given. The idea of a similar extension of
the duality theory for optimization problems is given.On a conic approach to convex analysis.
http://repub.eur.nl/pub/11706/
Tue, 18 Mar 2008 00:00:01 GMT<div>J. Brinkhuis</div>
Abstract. The aim of this paper is to make an attempt to justify the main results from Convex Analysis by one elegant tool, the conification method, which consists of three steps: conify, work with convex cones, deconify. It is based on the fact that the standard operations and facts (`the calculi') are much simpler for special convex sets, convex cones. By considering suitable classes of convex cones, we get the standard operations and facts for all situations in the complete generality that is required. The main advantages of this conification method are that the standard operations---linear image, inverse linear image, closure, the duality operator, the binary operations and the inf-operator---are defined on all objects of each class of convex objects---convex sets, convex functions, convex cones and sublinear functions---and that moreover the standard facts---such as the duality theorem---hold for all closed convex objects. This requires that the analysis is carried out in the context of convex objects over cosmic space, the space that is obtained from ordinary space by adding a horizon, representing the directions of ordinary space.Descent: An optimization point of view on different fields
http://repub.eur.nl/pub/19260/
Thu, 16 Aug 2007 00:00:01 GMT<div>J. Brinkhuis</div>
The aim of this paper is to present a novel, transparent approach to a well-established field: the deep methods and applications of the complete analysis of continuous optimization problems. Standard descents give a unified approach to all standard necessary conditions, including the Lagrange multiplier rule, the Karush–Kuhn–Tucker conditions and the second order conditions. Nonstandard descents lead to new necessary conditions. These can be used to give surprising proofs of deep central results of fields that are generally viewed as distinct from optimization: the fundamental theorem of algebra, the maximum and the minimum principle of complex function theory, the separation theorems for convex sets, the orthogonal diagonalization of symmetric matrices and the implicit function theorem. These optimization proofs compare favorably with the usual proofs and are all based on the same strategy. This paper is addressed to all practitioners of optimization methods from many fields who are interested in fully understanding the foundations of these methods and of the central results above.Duality and calculus of convex objects (theory and applications)
http://repub.eur.nl/pub/58825/
Mon, 01 Jan 2007 00:00:01 GMT<div>J. Brinkhuis</div><div>V. Tikhomirov</div>
A new approach to convex calculus is presented, which allows one to treat from a single point of view duality and calculus for various convex objects. This approach is based on the possibility of associating with each convex object (a convex set or a convex function) a certain convex cone without loss of information about the object. From the duality theorem for cones duality theorems for other convex objects are deduced as consequences. The theme 'Duality formulae and the calculus of convex objects' is exhausted (from a certain precisely formulated point of view).Optimalisering in financiering, economie en wiskunde: welke toepassingen zijn overtuigend?
http://repub.eur.nl/pub/7023/
Mon, 07 Nov 2005 00:00:01 GMT<div>J. Brinkhuis</div>
In deze paper wordt de stelling onderbouwd dat er drie redenen zijn waarom een toepassing van optimaliseringsmethoden overtuigend is: `nut', `inzicht' en `diepte'. Ieder van de drie wordt geillustreerd met eenkarakteristiek voorbeeld: de prijsformule voor opties van Black en Scholes (`nut'), het werk van Kydland en Presscot (`inzicht') en een bewijs van de hoofdstelling van de algebra (`diepte').A simple view on convex analysis and its applications
http://repub.eur.nl/pub/7024/
Thu, 03 Nov 2005 00:00:01 GMT<div>J. Brinkhuis</div><div>V. Tikhomirov</div>
Our aim is to give a simple view on the basics and applications of convex analysis. The essential feature of this account is the systematic use of the possibility to associate to each convex object---such as a convex set, a convex function or a convex extremal problem--- a cone, without loss of information. The core of convex analysis is the possibility of the dual description of convex objects, geometrical and algebraical, based on the duality of vectorspaces; for each type of convex objects, this property is encoded in an operator of duality, and the name of the game is how to calculate these operators. The core of this paper is a unified presentation, for each type of convex objects, of the duality theorem and the complete list of calculus rules.
Now we enumerate the advantages of the `cone'-approach. It gives a unified and transparent view on the subject. The intricate rules of the convex calculus all flow naturally from one common source. We have included for each rule a precise description of the weakest convenient assumption under which it is valid. This appears to be useful for applications; however, these assumptioons are usually not given. We explain why certain convex objects have to be excluded in the definition of the operators of duality: the collections of associated cones of the target of an operator of duality need not be closed (here `closed' is meant in an algebraic sense). This makes clear that the remedy is to take the closure of the target. As a byproduct of the cone approach, we have found the solution of the open problem of how to use the polar operation to give a dual description of arbitrary convex sets.
The approach given can be extended to the infinite-dimensional case.Novel insights into the multiplier rule
http://repub.eur.nl/pub/7026/
Thu, 29 Sep 2005 00:00:01 GMT<div>J. Brinkhuis</div><div>V. Protassov</div>
We present the Lagrange multiplier rule, one of the basic optimization methods, in a new way. Novel features include:
• Explanation of the true source of the power of the rule: reversal of tasks, but not the use of multipliers.
• A natural proof based on a simple picture, but not the usual technical derivation from the implicit function theorem.
• A practical method to avoid the cumbersome second order conditions.
• Applications from various areas of mathematics, physics, economics.
• Some hnts on the use of the rule.Matrix convex functions with applications to weighted centers for semidefinite programming
http://repub.eur.nl/pub/7025/
Wed, 31 Aug 2005 00:00:01 GMT<div>J. Brinkhuis</div><div>Z-Q. Luo</div><div>S. Zhang</div>
In this paper, we develop various calculus rules for general smooth matrix-valued functions and for the class of matrix convex (or concave) functions first introduced by Loewner and Kraus in 1930s. Then we use these calculus rules and the matrix convex function -log X to study a new notion of weighted convex centers for semidefinite programming (SDP) and show that, with this definition, some known properties of weighted centers for linear programming can be extended to SDP. We also show how the calculus rules for matrix convex functions can be used in the implementation of barrier methods for optimization problems involving nonlinear matrix functions.A comprehensive view on optimization: reasonable descent
http://repub.eur.nl/pub/6852/
Fri, 10 Jun 2005 00:00:01 GMT<div>J. Brinkhuis</div>
Reasonable descent is a novel, transparent approach to a well-established field: the deep methods and applications of the complete analysis of continuous optimization problems. Standard reasonable descents give a unified approach to all standard necessary conditions, including the Lagrange multiplier rule, the Karush-Kuhn-Tucker conditions and the second order conditions. Nonstandard reasonable descents lead to new necessary conditions. These can be used to give surprising proofs of deep central results outside optimization: the fundamental theorem of algebra, the maximum and the minimum principle of complex function theory, the separation theorems for convex sets, the orthogonal diagonalization of symmetric matrices and the implicit function theorem. These optimization proofs compare favorably with the usual proofs and are all based on the same strategy. This paper is addressed to all practitioners of optimization methods from many fields who are interested in fully understanding the foundations of these methods and of the central results above.On the universal method to solve extremal problems
http://repub.eur.nl/pub/1903/
Fri, 07 Jan 2005 00:00:01 GMT<div>J. Brinkhuis</div>
Some applications of the theory of extremal problems to mathematics and economics are made more accessible to non-experts.
1.The following fundamental results are known to all users of mathematical techniques, such as economist, econometricians, engineers and ecologists: the fundamental theorem of algebra, the Lagrange multiplier rule, the implicit function theorem, separation theorems for convex sets, orthogonal diagonalization of symmetric matrices. However, full explanations, including rigorous proofs, are only given in relatively advanced courses for mathematicians. Here, we offer short ans easy proofs. We show that akk these results can be reduced to the task os solving a suitable extremal problem. Then we solve each of the resulting problems by a universal strategy.
2. The following three practical results, each earning their discoverers the Nobel prize for Economics, are known to all economists and aonometricians: Nash bargaining, the formula of Black and Scholes for the price of options and the models of Prescott and Kydland on the value of commitment. However, the great value of such applications of the theory of extremal problems deserves to be more generally appreciated. The great impact of these results on real life examples is explained. This, rather than mathematical depth, is the correct criterion for assessing their value.On the complexity of the primal self-concordant barrier method
http://repub.eur.nl/pub/69328/
Sat, 01 Nov 2003 00:00:01 GMT<div>J. Brinkhuis</div>
The theory of self-concordance, initiated by Nesterov and Nemirovskii, has become very popular in recent years. In this paper an lnν reduction of the complexity is given for finding the analytical center for a ν-self-concordant barrier. This center-finding step is a crucial one in the primal self-concordant barrier method.