DocumentCode
2265682
Title
Business process optimization using bio-inspired methods — Ants or bees intelligence?
Author
Pop, Cristina Bianca ; Chifu, Viorica Rozina ; Salomie, Ioan ; Kovacs, Tunde ; Niculici, Alexandru Nicolae ; Suia, Dumitru Samuel
Author_Institution
Dept. of Comput. Sci., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear
2012
fDate
Aug. 30 2012-Sept. 1 2012
Firstpage
65
Lastpage
71
Abstract
This paper presents two bio-inspired methods addressing the problem of business process optimization. We provide a comparative approach for optimal business process flow selection and resource allocation using two of the most important bio-inspired meta-heuristics: Ant Colony Optimization and Bee Colony Optimization. Our approach does not use predefined rules for making the decisions when selecting the flow in the business process model. Given a business process, our approach starts from the business goal and reconstructs the optimal process flow by going backwards in the process in an iterative manner and solving everything that needs to be done for that goal to be completed. This reconstruction is realized by combining the bio-inspired algorithms with resource allocation strategies. The bio-inspired optimizations have been comparatively evaluated on a set of manufacturing scenarios.
Keywords
ant colony optimisation; decision making; iterative methods; resource allocation; ant colony optimization; ant intelligence; bee colony optimization; bee intelligence; bio-inspired meta-heuristics; business goals; decision making; iterative process; manufacturing scenarios; optimal business process flow selection; resource allocation strategies; Biological system modeling; Context; Manufacturing; Optimization; Resource management; Ant Colony Optimization; Bee Colony Optimization; Business process optimization; resource allocation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computer Communication and Processing (ICCP), 2012 IEEE International Conference on
Conference_Location
Cluj-Napoca
Print_ISBN
978-1-4673-2953-8
Type
conf
DOI
10.1109/ICCP.2012.6356162
Filename
6356162
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