Research Reports from the Department of Operations

Document Type

Report

Publication Date

7-1-1970

Abstract

A considerable amount of work has been done in recent years on adapting the simplex method for linear programming to solving II large-scale specially structured linear programs. One class of methods which has proved to be quite useful in practice is the class of compact inverse methods ([16], Chapter 6). In these S methods, the special structure of the constraint matrix is 8 exploited to obtain a representation of the basis inverse matrix 1 which is more compact than the explicit inverse used in the revised simplex method. .Early proposals for this type of algorithm are found in [1] and [5]. The product form of the inverse, which is used in commercially available linear programming packages and the modifications of it for variables with upper bounds [4] are the most widely used compact inverse methods. In 1964 Dantzig and Van Slyke [7] developed the generalized upper bounding algorithm for problems "with M+L equations, L of which have the property that each variable has at most one nonzero coefficient in them" [7] . This algorithm has been programmed in commercially available packages and has proved to be attractive for some problems [9].

Keywords

Operations research, Linear programming, Algorithms, Poisson processes, Doubly stochastic, Production scheduling, Matrices

Publication Title

Technical Memorandums from the Department of Operations, School of Management, Case Western Reserve University

Issue

Technical memorandum no. 196

Rights

This work is in the public domain and may be freely downloaded for personal or academic use

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