LINEAR PROGRAMMING TECHNIQUES FOR REGRESSION ANALYSIS

1958 ◽  
Author(s):  
Harvey M. Wagner
Keyword(s):  
Linear Programming ◽  
Regression Analysis ◽  
Programming Techniques

Linear Programming Techniques for the Construction of Palatable Human Diets

1994 ◽  
Vol 45 (5) ◽  
pp. 489-496 ◽  
Author(s):  
L. R. Fletcher ◽  
P. M. Soden ◽  
A. S. I. Zinober
Keyword(s):  
Linear Programming ◽  
Programming Techniques

An Integer Linear Programming-Based Method for the Extraction of Ontology Alignment

2021 ◽  
Vol 16 (2) ◽  
pp. 25-44
Author(s):  
Naima El Ghandour ◽  
Moussa Benaissa ◽  
Yahia Lebbah
Keyword(s):  
Linear Programming ◽  
Semantic Web ◽  
Integer Linear Programming ◽  
New Method ◽  
Ontology Matching ◽  
Ontology Alignment ◽  
Programming Techniques ◽  
Data Heterogeneity ◽  
Series Of Experiments

The Semantic Web uses ontologies to cope with the data heterogeneity problem. However, ontologies become themselves heterogeneous; this heterogeneity may occur at the syntactic, terminological, conceptual, and semantic levels. To solve this problem, alignments between entities of ontologies must be identified. This process is called ontology matching. In this paper, the authors propose a new method to extract alignment with multiple cardinalities using integer linear programming techniques. The authors conducted a series of experiments and compared them with currently used methods. The obtained results show the efficiency of the proposed method.

Strategic Choice and Data Envelopment Analysis: Comparing Computers across Many Attributes

1994 ◽  
Vol 9 (1) ◽  
pp. 61-69 ◽  
Author(s):  
John Doyle ◽  
Rodney Green
Keyword(s):  
Linear Programming ◽  
Regression Analysis ◽  
Data Envelopment Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Strategic Choice ◽  
Programming Approach ◽  
Data Envelopment ◽  
Linear Programming Approach

A linear programming approach (Data Envelopment Analysis) is described to determine the relative merits of a set of multi-input, multi-output systems, in which more output for less input is considered good. The method is applied to benchmarks of microcomputers, and is contrasted with a multiple regression analysis of the same data. It is also argued that the essence of two opposing strategic outlooks can be captured within the method.

Multivariate product-type lower bounds

2001 ◽  
Vol 38 (02) ◽  
pp. 407-420
Author(s):  
Henry W. Block ◽  
Tuhao Chen
Keyword(s):  
Linear Programming ◽  
Graph Theory ◽  
Lower Bounds ◽  
Product Type ◽  
Probability Inequalities ◽  
Programming Techniques

Univariate probability inequalities have received extensive attention. It has been shown that under certain conditions, product-type bounds are valid and sharper than summation-type bounds. Although results concerning multivariate inequalities have appeared in the literature, product-type bounds in a multivariate setting have not yet been studied. This note explores an approach using graph theory and linear programming techniques to construct product-type lower bounds for the probability of the intersection among unions of k sets of events.

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