A p-Median Model for Assortment and Trim Loss Minimization with an Application to the Glass Industry

One of the main issues in the glass industry is the minimization of the trim loss generated when cutting large parts (stocks) into small items. In our application stocks are produced in the plant. Many distinct stock sizes are feasible, and technical constraints limit the variety of cutting patterns to those producing a single type … Read more

Computational Enhancements in Low-Rank Semidefinite Programming

We discuss computational enhancements for the low-rank semidefinite programming algorithm, including the extension to block semidefinite programs, an exact linesearch procedure, and a dynamic rank reduction scheme. A truncated Newton method is also introduced, and several preconditioning strategies are proposed. Numerical experiments illustrating these enhancements are provided. Citation Manuscript, Department of Mangagement Sciences, University of … Read more

A direct formulation for sparse PCA using semidefinite programming

We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its eigenvector. The problem arises in the decomposition of a covariance matrix into sparse factors, and has wide applications ranging from biology to finance. We use a modification … Read more

Constrained optimization in seismic reflection tomography: an SQP augmented Lagrangian approach

Seismic reflection tomography is a method for determining a subsurface velocity model from the traveltimes of seismic waves reflecting on geological interfaces. From an optimization viewpoint, the problem consists in minimizing a nonlinear least-squares function measuring the mismatch between observed traveltimes and those calculated by ray tracing in this model. The introduction of a priori … Read more

Robust Capacity Expansion of Transit Networks

In this paper we present a methodology to decide capacity expansions for a transit network that finds a robust solution with respect to the uncertainty in demands and travel times. We show that solving for a robust solution is a computationally tractable problem under conditions that are reasonable for a transportation system. For example, the … Read more

Fuzzy Modeling with Adaptive Simulated Annealing

A new method for data-based fuzzy system modeling is presented. The approach uses Takagi-Sugeno models and Adaptive Simulated Annealing (ASA) to achieve its goal . The problem to solve is well defined – given a training set containing a finite number of input-output pairs, construct a fuzzy system that approximates the behavior of the real … Read more