NDLI: Basic Ant Colony Optimization

Content Provider	IEEE Xplore Digital Library
Author	Ying Pei Wenbo Wang Song Zhang
Copyright Year	2012
Abstract	Recently, the application of Ant Colony Optimization is much wider and it is always the highlight of key algorithm. There are also many improvements about the ACO algorithm, such as: the improvements of algorithm in self-adaptive, the improvements of increasing the diversity of various group, the improvements of enhancing local search, combining with the global optimization algorithm, and combining with deterministic local optimization algorithm, etc. However, with the developments of the theory and technology in multicore computing, how to implement ACO efficiently and parallel in a multicore computing environment being a new challenge for all researchers. This paper will propose a new ACO algorithm based on the multicore computing environment. The ACO is the probability algorithm used for searching optimization paths. It was proposed by Marco Dorigo in his doctoral dissertation in 1992, and the idea was from the activities that ants explore ways when they are looking for food. ACO is a kind of simulated evolutionary algorithm, and it has many advantages based on the previous research. Point to the issue of the parameter optimized design in PID control, comparing the results of ACO design to the results of genetic algorithm design, the final results present that the ACO has the effectiveness and application value of a new simulated evolutionary optimization method[1-3]. Recently, the development of ACO has been researched and paid more attention by researchers in various fields[4-8]. There are also many improvements to the ACO algorithm, including: the improvements of algorithm in self-adaptive, the improvements of increasing the diversity of various group, the improvements of enhancing local search, combining with the global optimization algorithm, and combining with deterministic local optimization algorithm, etc. However, with the developments of the theory and technology in multicore computing, how to implement ACO efficiently and paralleled in a multicore computing environment being a new challenge for all researchers. This paper will propose a new ACO algorithm which is oriented the multicore computing based on the multicore computing environment.
Starting Page	665
Ending Page	667
File Size	137077
Page Count	3
File Format	PDF
ISBN	9781467306898
e-ISBN	9780769546476
DOI	10.1109/ICCSEE.2012.178
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Ant Colony Optimization Ant colony optimization Multy-core Multicore processing Diversity reception Cities and towns Educational institutions 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