Construction of Covariance Matrices with a specified Discrepancy Function Minimizer, with Application to Factor Analysis

The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function the corresponding minimizer of the discrepancy function has a specified value. Often construction of such matrices is a first step in Monte Carlo studies of statistical … Read more

A Robust Branch-Cut-and-Price Algorithm for the Heterogeneous Fleet Vehicle Routing Problem

This paper presents a robust branch-cut-and-price algorithm for the Heterogeneous Fleet Vehicle Routing Problem (HFVRP), vehicles may have distinct capacities and costs. The columns in the formulation are associated to q-routes, a relaxation of capacitated elementary routes that makes the pricing problem solvable in pseudo-polynomial time. Powerful new families of cuts are also proposed, which … Read more

Robust Branch-Cut-and-Price Algorithms for Vehicle Routing Problems

This article presents techniques for constructing robust Branch-Cutand-Price algorithms on a number of Vehicle Routing Problem variants. The word “robust” stress the effort of controlling the worst-case complexity of the pricing subproblem, keeping it pseudo-polynomial. Besides summarizing older research on the topic, some promising new lines of investigation are also presented, specially the development of … Read more

Estimating Bounds for Quadratic Assignment Problems Associated with Hamming and Manhattan Distance Matrices based on Semidefinite Programming

Quadratic assignment problems (QAPs) with a Hamming distance matrix of a hypercube or a Manhattan distance matrix of rectangular grids arise frequently from communications and facility locations and are known to be among the hardest discrete optimization problems. In this paper we consider the issue of how to obtain lower bounds for those two classes … Read more

SHOWCASE SCHEDULING AT FRED ASTAIRE EAST SIDE DANCE STUDIO

The ballroom dancing showcases at Fred Astaire East Side Dance Studio in Manhattan are held at least twice a year and provide the students with an environment for socializing, practice, and improvement. The most important part of a showcase organization is the construction of the dance presentations timetable, and, with the number of participants increasing … Read more

Value-at-Risk optimization using the difference of convex algorithm

Value-at-Risk (VaR) is an integral part of contemporary financial regulations. Therefore, the measurement of VaR and the design of VaR optimal portfolios are highly relevant problems for financial institutions. This paper treats a VaR constrained Markowitz style portfolio selection problem when the distribution of returns of the considered assets are given in the form of … Read more

Iterative Estimation Maximization for Stochastic Linear Programs with Conditional Value-at-Risk Constraints

We present a new algorithm, Iterative Estimation Maximization (IEM), for stochastic linear programs with Conditional Value-at-Risk constraints. IEM iteratively constructs a sequence of compact-sized linear optimization problems, and solves them sequentially to find the optimal solution. The problem size IEM solves in each iteration is unaffected by the size of random samples, which makes it … Read more

On-line Service Scheduling

This paper is concerned with a scheduling problem that occurs in service systems, where customers are classified as `ordinary’ and `special’. Ordinary customers can be served on any service facility, while special customers can be served only on the flexible service facilities. Customers arrive dynamically over time and their needs become known upon arrival. We … Read more

Passenger Name Record Data Mining Based Cancellation Forecasting for Revenue Management

Revenue management (RM) enhances the revenues of a company by means of demand-management decisions. An RM system must take into account the possibility that a booking may be canceled, or that a booked customer may fail to show up at the time of service (no-show). We review the Passenger Name Record data mining based cancellation … Read more

Parallel Space Decomposition of the Mesh Adaptive Direct Search algorithm

This paper describes a parallel space decomposition PSD technique for the mesh adaptive direct search MADS algorithm. MADS extends a generalized pattern search for constrained nonsmooth optimization problems. The objective of the present work is to obtain good solutions to larger problems than the ones typically solved by MADS. The new method PSD-MADS is an … Read more