DocumentCode :
1755968
Title :
GARO Framework: A Genetic Algorithm Based Resource Optimization for Organizational Efficiency
Author :
Saha, Simanto
Author_Institution :
Stern Sch. of Bus., New York Univ., New York, NY, USA
Volume :
7
Issue :
4
fYear :
2013
fDate :
Dec. 2013
Firstpage :
889
Lastpage :
895
Abstract :
Organizations strive to gain efficiency, which is often measured by its outputs. However, this approach consists partly of the whole effort to maximize organizational efficiency. The component that is seldom considered is the optimal allocation of tasks to resources, as this has a critical impact on the outputs of the organization. An efficient allocation of tasks to resources would have a direct bearing on the efficiency of the organization. Nevertheless, organizations seldom conduct this with a scientific basis, assuming that there is not much analysis required or possible. The research that has been undertaken in this area has significant deficiencies and lacks practicality. In this paper, an innovative method that utilizes a genetic algorithm technique to optimally utilize organizational resources is presented.
Keywords :
genetic algorithms; organisational aspects; resource allocation; GARO framework; genetic algorithm based resource optimization; innovative method; organizational efficiency; organizational resource utilization; task optimal allocation; Genetic algorithms; Optimization; Organizations; Resource management; Sociology; Statistics; Genetic algorithm (GA); PEN analysis; organizational efficiency; resource optimization;
fLanguage :
English
Journal_Title :
Systems Journal, IEEE
Publisher :
ieee
ISSN :
1932-8184
Type :
jour
DOI :
10.1109/JSYST.2012.2223535
Filename :
6378393
Link To Document :
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