Richard S. Barr

Designing and reporting on computational experiments with heuristic methods

This article discusses the design of computational experiments to test heuristic methods and provides reporting guidelines for such experimentation. The goal is to promote thoughtful, well-planned, and extensive testing of heuristics, full disclosure of experimental conditions, and integrity in and reproducibility of the reported results.

Evaluating the productive efficiency and performance of US commercial banks

Reviews previous research on the efficiency and performance of financial institutions and uses Siems and Barr’s (1998) data envelopment analysis (DEA) model to evaluate the relative productive efficiency of US commercial banks 1984‐1998. Explains the methodology, discusses the input and output measures used and relates bank performance measures to efficiency. Describes the CAMELS rating system used by bank examiners and regulators; and finds that banks with high efficiency scores also have strong CAMELS ratings. Summarizes the other relationship identified and recommends the use of DEA to help analysts and policy makers understand organizations in greater depth, regulators and examiners to develop monitoring tools and banks to benchmark their processes.

THE ALTERNATING BASIS ALGORITHM FOR ASSIGNMENT PROBLEMS

The purpose of this paper is to present a new primal extreme point algorithm for solving assignment problems which both circumvents and exploits degeneracy. The algorithm is based on the observation that the degeneracy difficulties of the simplex method result from the unnecessary inspection of alternative basis representations of the extreme points. This paper characterizes a subsetQ of all bases that are capable of leading to an optimal solution to the problem if one exists. Using this characterization, an extreme point algorithm is developed which considers only those bases inQ. Computational results disclose that the new algorithm is substantially more efficient than previously developed primal and primal-dual extreme point (“simplex”) methods for assignment problems.

A New Optimization Method for Large Scale Fixed Charge Transportation Problems

This paper presents a branch-and-bound algorithm for solving fixed charge transportation problems where not all cells exist. The algorithm exploits the absence of full problem density in several ways, thus yielding a procedure which is especially applicable to solving real world problems which are normally quite sparse. Additionally, streamlined new procedures for pruning the decision tree and calculating penalties are presented. We present computational experience with both a set of large test problems and a set of dense test problems from the literature. Comparisons with other codes are uniformly favorable to the new method, which runs more than twice as fast as the best alternative.

An improved version of the out-of-kilter method and a comparative study of computer codes

The primary objectives of this paper are: (1) to present an improved formulation of the out-of-kilter algorithm; (2) to give the results of an extensive computational comparison of a code based on this formulation with three widely-used out-of-kilter production codes; (3) to study the possible sensitivity of these programs to the type of problem being solved; and (4) to investigate the effect of advanced dual start procedures on overall solution time.The study discloses that the new formulation does indeed provide the most efficient solution procedure of those tested. This streamlined version of out-of-kilter was found to be faster than the other out-of-kilter codes tested (SHARE, BSRL and Texas Water Development Board codes) by a factor of 2–5 on small and medium size problems and by a factor of 4–15 on large problems. The streamlined methods median solution time for 1500 node networks on a CDC 6600 computer is 33 seconds with a range of 33 to 35 seconds.

An envelopment-analysis approach to measuring the managerial efficiency of banks

The dramatic rise in bank failures over the last decade has led to a search for leading indicators so that costly bailouts might be avoided. While the quality of a banks management is generally acknowledged to be a key contributor to institutional collapse, it is usually excluded from early warning models for lack of a metric. This paper presents a new approach for quantifying a banks managerial efficiency, using a data-envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency and quality. An analysis of 930 banks over a five-year period shows significant differences in management-quality scores between surviving and failing institutions. These differences are detectable long before failure occurs and increase as the failure date approaches. Hence this new metric provides an important, yet previously missing, modelling element for the early identification of troubled banks.

Forecasting Bank Failure: A Non-Parametric Frontier Estimation Approach

The dramatic rise in bank failures over the last decade has led to a search for leading indicators so that costly bailouts might be avoided. While the quality of a banks management is generally acknowledged to be a key contributor to institutional collapse, it is usually excluded from early-warning models for lack of a metric. This paper describes a new approach for quantifying a banks managerial efficiency, using a data- envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency. This new metric captures an elusive, yet crucial, element of institutional success: management quality. New failure-prediction models for detecting a banks troubled status which incorporate this explanatory variable have proven to be robust and accurate, as verified by in-depth empirical evaluations, cost sensitivity analyses, and comparisons with other published approaches

Enhancements of Spanning Tree Labeling Procedures for Network Optimization.

Abstract : New labeling techniques are provided for accelerating the basis exchange step of specialized linear programming methods for network problems. Computational results are presented which show that these techniques substantially reduce the amount of computation involved in updating operations. (Author)

Dynamic Wavelength Routing in WDM Networks via Ant Colony Optimization

This study considers the routing and wavelength assignment problem (RWA) in optical wavelength-division-multiplexed networks. The focus is dynamic traffic, in which the number of wavelengths per fiber is fixed. We minimize connection blocking using an ant-colony-optimization (ACO) algorithm that quantifies the importance of combining path-length and congestion information in making routing decisions to minimize total network connection blocking. The ACO algorithm achieves lower blocking rates than an exhaustive search over all available wavelengths for the shortest path.

Parallel and hierarchical decomposition approaches for solving large-scale Data Envelopment Analysis models

Accompanying the increasing popularity of DEA are computationally challenging applications: large-scale problems involving the solution of thousands of linear programs. This paper describes a new problem decomposition procedure which dramatically expedites the solution of these computationally intense problems and fully exploits parallel processing environments. Testing of a new DEA code based on this approach is reported for a wide range of problems, including the largest reported to date: an 8,700-LP banking-industry application.