Genetic Algorithms for Organizational Design and Inspired by Organizational Theory

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Modularity is widely used in system analysis and design such as complex engineering products and their organization, and modularity is also the key to solving optimization problems efficiently via problem decomposition. We first discover modularity in a system and then leverage this knowledge to improve the performance of the system. In this chapter, we tackle both problems with the alliance of organizational theory and evolutionary computation. First, we cluster the dependency structure matrix (DSM) of a system using a simple genetic algorithm (GA) and an information theoretic-based metric. Then we design a better GA through the decomposition of the optimization problem using the proposed DSM clustering method.

Original languageEnglish
Title of host publicationHandbook of Research on Nature-Inspired Computing for Economics and Management
Subtitle of host publicationVolume I-II
Pages412-428
Number of pages17
VolumeII
ISBN (Electronic)9781591409854
DOIs
StatePublished - 1 Jan 2006

Fingerprint

Dive into the research topics of 'Genetic Algorithms for Organizational Design and Inspired by Organizational Theory'. Together they form a unique fingerprint.

Cite this