CLUSTER ANALYSIS AND MATHEMATICAL PROGRAMMING

reportActive / Technical Report | Accession Number: AD0697267 | Open PDF

Abstract:

Cluster analysis involves the problem of optimal partitioning of a given set of entities into a pre-assigned number of mutually exclusive and exhaustive clusters. Here the problem is formulated in two different ways with the distance function a of minimizing the within groups sums of squares and b minimizing the maximum distance within groups. These lead to different kinds of linear and non-linear 0-1 integer programming problems. Computational difficulties are discussed.

Author(s):
Rao, M. R.
Author Organization(s):
CARNEGIE-MELLON UNIV PITTSBURGH PA MANAGEMENT SCIENCES RESEARCH GROUP
Descriptive Note:
Research rept.
Supplementary Note:
DOI: 10.21236/AD0697267
Pagination:
0030

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release, Document Partially Illegible
Distribution Statement:
Approved For Public Release; Distribution Is Unlimited. Document Partially Illegible.

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
RR-183
Contract/Grant Number(s):
NONR-760(24)
Project Number(s):
NR-047-048
Monitor Series:
ONR
 Subject Terms
Joint Capability Areas:
JCA_1_Force Support; JCA_5.3_Planning; JCA_5_Command and Control; JCA_1.2_Force Preparation; JCA_1.2.3_Educating; JCA_1.3_Human Capital Management; JCA_1.3.2_Personnel Management; JCA_8.2.4_Leverage Capacities and Capabilities of Security Establishments; JCA_8.2_Shape; JCA_8_Building Partnerships; JCA_1.2.5_Lessons Learned
Modernization Areas:
AI and Machine Learning
Communities of Interest:
Materials and Manufacturing Processes
Descriptor(s):
*MATHEMATICAL PROGRAMMING, *STATISTICAL ANALYSIS, ALGORITHMS, OPTIMIZATION, GROUPS(MATHEMATICS), NONLINEAR PROGRAMMING, CLASSIFICATION, LINEAR PROGRAMMING
Field(s)/Group(s):
Statistics and Probability, Operations Research
Keyword(s):
*BRANCH AND BOUND METHOD, *CLUSTER ANALYSIS, *MATHEMATICAL PROGRAMMING
Report Date:
1969 Oct 01