Capacitated Facility Location Model with Risk Pooling

The Facility Location Model with Risk Pooling (LMRP) extends the uncapacitated fixed charge model to incorporate inventory decisions at the distribution centers (DCs). In this paper, we introduce a capacitated version of the LMRP that handles inventory management at the DCs such that the capacity limitations at the DCs are not exceeded. We consider a … Read more

KNITRO-Direct: A Hybrid Interior Algorithm for Nonlinear Optimization

A hybrid interior-point method for nonlinear programming is presented. It enjoys the flexibility of switching between a line search based method which computes steps by factoring the primal-dual equations and an iterative method using a conjugate gradient algorithm and globalized by means of trust regions. Steps computed by a direct factorization are always tried first, … Read more

On a class of minimax stochastic programs

For a particular class of minimax stochastic programming models, we show that the problem can be equivalently reformulated into a standard stochastic programming problem. This permits the direct use of standard decomposition and sampling methods developed for stochastic programming. We also show that this class of minimax stochastic programs subsumes a large family of mean-risk … Read more

Intermediate Report on the development of an optimization code for smooth, high computing load, continuous objective functions when derivatives are not available

We find very often in the industry simulators of huge chemical reactors, simulators of huge turbo-compressors, simulators of the path of a satellite in low orbit around earth, … These simulators were written to allow the design engineer to correctly estimate the consequences of the adjustment of one (or many) design variables (or parameters of … Read more

Double-Regularization Proximal Methods, with Complementarity Applications

We consider the variational inequality problem formed by a general set-valued maximal monotone operator and a possibly unbounded “box” in $R^n$, and study its solution by proximal methods whose distance regularizations are coercive over the box. We prove convergence for a class of double regularizations generalizing a previously-proposed class of Auslender et al. We apply … Read more

The continuous Newton-Raphson method can look ahead

This paper is about an intriguing property of the continuous Newton-Raphson method for the minimization of a continuous objective function f: if x is a point in the domain of attraction of a strict local minimizer x* then the flux line of the Newton-Raphson flow that starts in x approaches x* from a direction that … Read more

Convergence of string-averaging projection schemes for inconsistent convex feasibility problems

We study iterative projection algorithms for the convex feasibility problem of finding a point in the intersection of finitely many nonempty, closed and convex subsets in the Euclidean space. We propose (without proof) an algorithmic scheme which generalizes both the string-averaging algorithm and the block-iterative projections (BIP) method with fixed blocks and prove convergence of … Read more

Polyhedral investigations on stable multi-sets

Stable multi-sets are an evident generalization of the well-known stable sets. As integer programs, they constitute a general structure which allows for a wide applicability of the results. Moreover, the study of stable multi-sets provides new insights to well-known properties of stable sets. In this paper, we continue our investigations started in Koster and Zymolka … Read more

A Wide Interval for Efficient Self-Scaling Quasi-Newton Algorithms

This paper uses certain conditions for the global and superlinear convergence of the two-parameter self-scaling Broyden family of quasi-Newton algorithms for unconstraiend optimization to derive a wide interval for self-scaling updates. Numerical testing shows that such algorithms not only accelerate the convergence of the (unscaled) methods from the so-called convex class, but increase their chances … Read more

Optimization of A Fed-batch Fermentation Process Control Competition Problem Using NEOS

An optimal control solution to a fed-batch fermentation process, responding to a competition call, was developed using NEOS Server. Substantial improvement to the nominal performance achieved in the paper demonstrates the ability of the NEOS Server and the APPS algorithm. Citation Proceedings of Inst. of Mechanical Engineers , Part-I (UK). To appear. (Accepted May 2003). … Read more