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A Clustering Algorithm for Computer‐Assisted Process Organization
Author(s) -
Aronson Jay E.,
Klein Gary
Publication year - 1989
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1989.tb01416.x
Subject(s) - cluster analysis , computer science , process (computing) , algorithm , group (periodic table) , data mining , artificial intelligence , programming language , chemistry , organic chemistry
Amathematical programming clustering model that forms groups based on total group membership interactions is extended to include precedence relationships, group size limits, and group time limits. The extended clustering model is most appropriate for structured design of information systems as described by the computer‐assisted process organization (CAPO), which requires certain ordering and may have limits on development and production capacity. An efficient algorithm for optimizing the CAPO criteria along with computational results is presented. The results show that the method is viable for the CAPO problems reported in the literature.