A clustering method using new modularity indices and a genetic algorithm: With extended Chromosomes

Sangjin Jung, Timothy W. Simpson

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Module definition entails clustering a product architecture into independent or coordinated modules. Clustering algorithms based on Design Structure Matrices (DSMs) for defining modules have been widely studied. After reviewing existing clustering algorithms, we introduce simple new metrics that can be used as modularity indices bounded between 0 and 1 and also utilized as the objective functions to obtain optimal DSMs by maximizing interactions within modules and interactions between modules. As a search strategy for clustering modules, a combinatorial genetic algorithm using a new extended chromosome approach and modified operators for the chromosome is suggested. The module definition results indicated that the proposed clustering method using new modularity indices and genetic algorithm helps obtain optimal modular product architectures more logically. CLUSTERING Techniques Development.

Original languageEnglish (US)
Pages (from-to)38-45
Number of pages8
JournalJournal of Modern Project Management
Volume3
Issue number2
StatePublished - Sep 1 2015

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management of Technology and Innovation

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