44 research outputs found

    Not All Firms Are Created Equal: SMEs and Vocational Training in the UK, Italy, and Germany

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    Why do skill formation systems put SMEs at greater disadvantage in some countries than others vis-à-vis large employers? By comparing vocational education and training (VET) institutions and their differential effect on firms of different sizes across three countries (UK, Italy, and Germany), we show that the design of VET has profound implications for shaping the ability of SMEs to use institutions as resources. In particular, quasi-market institutions in the UK amplify SMEs’ disadvantage, while non-market coordinating institutions in Italy and Germany narrow the gap between SMEs and large employers. By unpacking the comparative disadvantage of SMEs, we offer important nuances to the argument that institutions help firms coordinate their business activities in different varieties of capitalism.Warum erfahren kleine und mittelständische Unternehmen (KMU) durch Berufsbildungssysteme mehr Nachteile als große Unternehmen und warum ist dieser Unterschied in manchen Ländern größer als in anderen? Wir vergleichen Ausbildungsinstitutionen und ihren unterschiedlichen Effekt auf Firmen verschiedener Größe in drei Ländern (Großbritannien, Italien und Deutschland). Dabei zeigen wir, dass die Art der Institutionen die Möglichkeit von Firmen, die vorhandenen Institutionen als Ressource zu nutzen, beeinflusst. Insbesondere verstärken die in Großbritannien vorherrschenden quasimarktlichen Institutionen den Nachteil von KMU, wohingegen nichtmarktliche Institutionen in Italien und Deutschland den Unterschied zu großen Unternehmen verringern. Durch das Aufzeigen des komparativen Nachteils von KMU leistet unser Papier einen Beitrag zu einer nuancierteren Sichtweise der Rolle von Institutionen in verschiedenen Spielarten des Kapitalismus.1 Introduction 2 Institutions, firms, and training 3 Puzzle and argument 4 Methodology 5 Findings The United Kingdom Italy Germany 6 Discussion and conclusion Appendix Reference

    Indefinitely preconditioned conjugate gradient method for large sparse equality and inequality constrained quadratic problems

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    This paper is concerned with the numerical solution of a symmetric indefinite system which is a generalization of the Karush Kuhn Tucker system. Following the recent approach of Luk.san and Vl.cek, we propose to solve this system by a preconditioned conjugate gradient (PCG) algorithm and we devise two indefin ite preconditioners with good theoretical properties. In particular, for one of these preconditioners, the finite termination property of the PCG method is stated. The PCG method combined with a parallel version of these preconditioners is used as inner solver within an inexact Interior-Point (IP) method for the solution of large and sparse quadratic programs. The numerical results obtained by a parallel code implementing the IP method on distributed memory multiprocessor systems enable us to confirm the effectiveness of the proposed approach for problems with special structure in the constraint matrix and in the objective function

    Solution of discrete optimal control problems via mathematical programming

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    In this paper we consider the solution of discrete optimal control problems via mathematicalprogramming. In particular we examine iterative schemes, such as Hestenes' method of multipliers and interior-point method, which are suitable for linear-quadratic optimal control problems and for nonlinear optimal control problems respectively. Convergence results are reported as well as numerical evaluation of the effectiveness of these methods

    A Newton Inexact Interior-Point Method for Large Scale Nonlinear Optimization Problems

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    In this paper, we describe a variant of the Newton Interior{Point method in [8] for nonlinear programming problems. In this scheme, the perturbation parameter can be chosen within a range of values and we can use an iterative method for approximately solving the reduced linear system arising at each step. We have devised the inner termination rule which guarantees the global convergence of this Newton Inexact Interior-Point method. We remark that the required assumptions are weaker than those stated in [8], as shown by some numerical examples

    Nonlinear programming methods for solving optimal control problems

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    This paper concerns with the problem of solving optimal control problems by means of nonlinear programming methods. The technique employed to obtain a mathematical programming problem from an optimal control problem is explained and the Newton interior-point method, chosen for its solution, is presented with special regard to the choice of the involved parameters. An analysis of the behaviour of the method is reported on four optimal control problems, related to improving water quality in an aeration process and to the study of diffusion convection processes

    Global convergence of the Newton interior-point method for nonlinear programming

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    The aim of this paper is to show that the theorem on the global convergence of the Newton interior-point (IP) method presented in Ref. 1 can be proved under weaker assumptions. Indeed, we assume the boundedness of the sequences of multipliers related to nontrivial constraints, instead of the hypothesis that the gradients of the inequality constraints corresponding to slack variables not bounded away from zero are linear independent. By numerical examples, we show that, in the implementation of the Newton IP method, loss of boundedness in the iteration sequence of the multipliers detects when the algorithm does not converge from the chosen starting point

    Some Applications via a Parallel Interior-Point Method

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    We report the results obtained by a parallel Interior-Point method combined with the Preconditioned Conjugate Gradient algorithm for the solution of some large-scale applications on Cray T3E and SGI Origin 2000. The first application concerns stochastic programming and robust optimization problems and the second one arises from a reformulation of a special class of discrete optimal control problems
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