An Overview of Supplier Rating, Certification and Selection Systems in the Defense Aircraft Industry

In this paper, we report on the status of supplier rating, certification and selection systems in the US Defense Aircraft Industry. Our findings result from a range of information gathering activities over the past eighteen months including: Site visits to companies; a one day review session at Lockheed Fort Worth Company on February 7, 1994 in which 10 companies made presentations of their systems; the study of documents received from over a dozen companies pertaining to rating, certification and selection systems; and, responses to the Survey of Supplier Systems and Relationships. The purposes of this report are: • To identify and review current practices with respect to supplier rating, certification and selection systems based on our current state of knowledge; • To discuss the extent to which these systems support the process of supplier base optimization

A Note on the Primal-Dual and Out-of-Kilter Algorithms for Network Optimization Problems

Not AvailableSupported in part by the U.S. Army Research Office (Durham) under Contract No. DAHC04-73-C-003

Future Directions of Large Scale Mixed Integer Programming

Not AvailableSupported in part by the U.S. Army Research Office (Durham) under contract No. DAAG29-76-C-0064

Convergent Duality for the Traveling Salesman Problem

A constructive method is presented for optimizing exactly the Traveling Salesman Problem as a sequence of shortest route problems. The method combines group theoretic and Lagrangean relaxation constructions. Key Words: Traveling Salesman Problem, Lagrangean relaxation, shortest route problem, generalized linear programming, group theory

A Note on Node Aggregation and Benders Decomposition

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An adaptive group theoretic algorithm for integer programming problems

At head of title: Preliminary draft

Generalized Linear Programming without Constraint Qualification

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Analyzing Multi-Objective Linear and Mixed Integer Programs by Lagrange Multipliers

A new method for multi-objective optimization of linear and mixed programs based on Lagrange multiplier methods is developed. The method resembles, but is distinct from, objective function weighting and goal programming methods. A subgradient optimization algorithm for selecting the multipliers is presented and analyzed. The method is illustrated by its application to a model for determining the weekly re-distribution of railroad cars from excess supply areas to excess demand areas, and to a model for balancing cost minimization against order completion requirements for a dynamic lot size model

Analyzing Multi-Objective Linear Programs by Lagrange Multipliers

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