NDLI: Quantum Evolutionary Algorithm based on Particle Swarm theory in multiobjective problems

Content Provider	IEEE Xplore Digital Library
Author	Hossain, M.K. Hossain, M.A. Hashem, M.M.A. Ali, M.M.
Copyright Year	2010
Description	Author affiliation: Dept. of Computer Science and Engineering, Khulna University of Engineering & Technology, Bangladesh (Hossain, M.K.; Hossain, M.A.; Hashem, M.M.A.; Ali, M.M.)
Abstract	Quantum Evolutionary Algorithm (QEA) is an optimization algorithm based on the concept of quantum computing and Particle Swarm Optimization (PSO) algorithm is a population based intelligent search technique. Both these techniques have good performance to solve optimization problems. PSEQEA combines the PSO with QEA to improve the performance of QEA and it can solve single objective optimization problem efficiently and effectively. In this paper, PSEQEA is studied to solve multi-objective Optimization (MO) problems. Some well-known non-trivial functions are used to observe the performance of PSEQEA to detect the Pareto optimal points and the shape of the Pareto front using both Fixed Weighted Aggregation method and Adaptive Weighted Aggregation method. Moreover, Vector Evaluated PSEQEA (VEPSEQEA) borrows concept from Schaffer's Vector Evaluated Genetic Algorithm (VEGA) that can also cope with MO problems. Simulation results show that PSEQEA and VEPSEQEA perform better than PSO and VEPSO to discover the Pareto frontier.
Starting Page	21
Ending Page	26
File Size	158107
Page Count	6
File Format	PDF
ISBN	9781424484966
e-ISBN	9781424484973
DOI	10.1109/ICCITECHN.2010.5723823
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-23
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Quantum computing Multi objective Optimization Quantum Evolutionary Algorithm Logic gates Weighted Aggregation method Particle swarm optimization Optimization Equations Biological cells Particle Swarm 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