NDLI: Business process optimization using bio-inspired methods

Content Provider	IEEE Xplore Digital Library
Author	Pop, C.B. Chifu, V.R. Salomie, I. Kovacs, T. Niculici, A.N. Suia, D.S.
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, Technical University of Cluj-Napoca, Romania (Pop, C.B.; Chifu, V.R.; Salomie, I.; Kovacs, T.; Niculici, A.N.; Suia, D.S.)
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.
Starting Page	65
Ending Page	71
File Size	158658
Page Count	7
File Format	PDF
ISBN	9781467329538
e-ISBN	9781467329521
DOI	10.1109/ICCP.2012.6356162
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-30
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Business process optimization Ant Colony Optimization resource allocation Biological system modeling Bee Colony Optimization Manufacturing Resource management Optimization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Towards Bio-Inspired Self-Organization in Sensor Networks: Applying the Ant Colony Algorithm

Sensor scheduling using ant colony optimization

Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown

Bioescenarios VI. bee colony

A Task Operation Model for Resource Allocation Optimization in Business Process Management

Self-organized manufacturing resource management: An ant-colony inspired approach

Software Reliability Prediction by Using Ant Colony Optimization Technique

Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown

Optimizing Resource Allocation in Manufacturing Project Based on Adaptive Ant Colony Algorithm

Business process optimization using bio-inspired methods — Ants or bees intelligence?

Similar Documents

Towards Bio-Inspired Self-Organization in Sensor Networks: Applying the Ant Colony Algorithm

Sensor scheduling using ant colony optimization

Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown

Bioescenarios VI. bee colony

A Task Operation Model for Resource Allocation Optimization in Business Process Management

Self-organized manufacturing resource management: An ant-colony inspired approach

Software Reliability Prediction by Using Ant Colony Optimization Technique

Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown

Optimizing Resource Allocation in Manufacturing Project Based on Adaptive Ant Colony Algorithm

Business process optimization using bio-inspired methods — Ants or bees intelligence?