Papers in this group
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In this paper, we propose heuristic approaches for solving master planning problems that arise in semiconductor manufacturing networks. The considered problem consists of determining appropriate wafer quantities for several products, facilities, and…
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We present a model for making master planning decisions in semiconductor manufacturing. The problem consists in determining appropriate wafer quantities for certain products, facilities (locations), and periods of time. Different demand types, i.e.,…
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We present a master planning problem that arises in semiconductor manufacturing. The problem consists in determining appropriate wafer quantities for several products, facilities, and periods of time. Different demand types, i.e. confirmed orders…
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The local convergence properties of a class of primal-dual interior point methods are analyzed. These methods are designed to minimize a nonlinear, nonconvex, objective function subject to linear equality constraints and general inequalities. They…
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In this paper, we examine the sensitivity of trust-region algorithms on the parameters related to the step acceptance and update of the trust region. We show, in the context of unconstrained programming, that the numerical efficiency of these…
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We introduce a new framework for the convergence analysis of a class of distributed constrained non-convex optimization algorithms in multi-agent systems. The aim is to search for local minimizers of a non-convex objective function which is supposed…
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We consider column sufficient linear complementarity problems and study the prob- lem of identifying those variables that are zero at a solution. To this end we propose a new, computa- tionally inexpensive technique that is based on growth…
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We examine the sequence of local minimizers of the log-barrier function for a nonlinear pro- gram near a solution at which second-order sufficient conditions and the Mangasarian-Fromovitz constraint qualification are satisfied, but the active…
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A technique for the resolution of degeneracy in an Active Set Method for Quadratic Programming is described. The approach generalises Fletcher's method [2] which applies to the LP case. The method is described in terms of an LCP tableau, which is…
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A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. Themethod uses a primal-dual trust-region model to ensure descent on a suitable merit…
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We introduce the OPAL framework in which the identification of good algorithmic parameters is interpreted as a black box optimization problem whose variables are the algorithmic parameters. In addition to the target algorithm, the user of the…
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Special methods for dealing with constraints of the formxj= xk, called variable upper bounds, were introduced by Schrage. Here we describe a method that circumvents the massive degeneracy inherent in these constraints and show how it can be…
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Aninterior-point method for nonlinear programming is presented. It enjoys the flexibility of switch- ing between a line search method that computes steps by factoring the primal-dual equations and a trust region method that uses a conjugate gradient…