NDLI: Multilevel optimization strategies based on metamodel-assisted evolutionary algorithms, for computationally expensive problems

Content Provider	IEEE Xplore Digital Library
Author	Kampolis, I.C. Zymaris, A.S. Asouti, V.G. Giannakoglou, K.C.
Copyright Year	2007
Description	Author affiliation: Nat. Tech. Univ. of Athens, Athens (Kampolis, I.C.; Zymaris, A.S.; Asouti, V.G.; Giannakoglou, K.C.)
Abstract	In this paper, three multilevel optimization strategies are presented and applied to the design of isolated and cascade airfoils. They are all based on the same general-purpose search platform, which employs hierarchical, distributed metamodel-assisted evolutionary algorithms (HDMAEAs). The core search engine is an evolutionary algorithm (EA) assisted by local metamodels (radial basis function networks) which, for each population member, are trained anew on a "suitable" subset of the already evaluated solutions. The hierarchical scheme has a two-level structure, although it may accommodate any number of levels. At each level, the user may link (a) a different evaluation tool, such as low or high fidelity discipline-specific software, (b) a different optimization method, selected amongst stochastic and deterministic algorithms and/or (c) a different set of design variables, according to coarse and fine problem parameterizations. In the aerodynamic shape optimization problems presented in this paper, the three aforementioned techniques resort on (a) Navier-Stokes and integral boundary layer solvers, (b) evolutionary and gradient- descent algorithms where the adjoint method computes the objective function gradient and (c) airfoil parameterizations with different numbers of Bezier control points. The EAs used at any level are coarse-grained distributed EAs with a different MAEA at each deme. The three variants of the HDMAEA can be used either separately or in combination, in order to reduce the CPU cost. The optimization software runs in parallel, on multiprocessor systems.
Starting Page	4116
Ending Page	4123
File Size	484598
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4425008
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Evolutionary computation Automotive components Optimization methods Shape control Design optimization Search engines Radial basis function networks Software tools Stochastic processes Software algorithms
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