Journal ArticleDOI
W. Dinkelbach, Sensitivitätsanalysen und parametrische Programmierung. (Ökonometrie und Unternehmensforschung, Band XII). XI + 190 S. Berlin/Heidelberg/New York 1969. Springer-Verlag. Preis geb. DM 48, - .
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This article is published in Zamm-zeitschrift Fur Angewandte Mathematik Und Mechanik.The article was published on 1970-01-01. It has received 74 citations till now.read more
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Journal ArticleDOI
Algorithm 39 Clusterwise linear regression
TL;DR: The combinatorial problem of clusterwise discrete linear approximation is defined as finding a given number of clusters of observations such that the overall sum of error sum of squares within those clusters becomes a minimum.
Journal ArticleDOI
Direct algorithms for checking consistency and making inferences from conditional probability assessments
TL;DR: General algorithms for making inferences from any finite collection of (possibly imprecise) conditional probabilities are provided to provide simple, direct solutions which can be implemented using linear programming algorithms.
CHAPTER 6 THE OPTIMAL SET AND OPTIMAL PARTITION ApPROACH TO LINEAR AND QUADRATIC PROGRAMMING
TL;DR: This chapter describes the optimal set approach for sensitivity analysis for LP and presents an algorithm to compute the partitions, optimal sets and the optimal value function.
Journal ArticleDOI
Linear Multiparametric Programming by Multicriteria Simplex Method
P. L. Yuf,Milan Zeleny +1 more
TL;DR: Yu, P.L., M.Z Zeleny as discussed by the authors used a new type of parametric space, which arises naturally in its formulation, and two computational methods are discussed, an indirect algebraic method which locates the corresponding set of all nondominated extreme points.
Book ChapterDOI
The Optimal Set and Optimal Partition Approach to Linear and Quadratic Programming
TL;DR: In this article, the optimal set approach was used for sensitivity analysis for linear programming and it was shown that optimal partitions and optimal sets remain constant between two consecutive transition points of the optimal value function.