Automated, Parallel Optimization of Stochastic Functions Using a Modified Simplex Algorithm

This paper proposes a framework and new parallel algorithm for optimization of stochastic functions based on a downhill simplex algorithm. The function to be optimized is assumed to be subject to random noise, the variance of which decreases with sampling time, this is the situation expected for man...

Full description

Saved in:
Bibliographic Details
Published in:2010 Sixth IEEE International Conference on E-Science Workshops pp. 98 - 103
Main Authors: Chahal, D, Stuart, S J, Goasguen, S, Trout, C J
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2010
Subjects:
Computational modeling
Noise
Noise measurement
Object oriented modeling
Optimization
parallel optimizaton
Servers
simplex
Stochastic processes
water model
ISBN:9781424489886, 1424489881
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This paper proposes a framework and new parallel algorithm for optimization of stochastic functions based on a downhill simplex algorithm. The function to be optimized is assumed to be subject to random noise, the variance of which decreases with sampling time, this is the situation expected for many real-world and simulation applications where results are obtained from sampling, and contain experimental error or random noise. The proposed optimization method is found to be comparable to previous stochastic optimization algorithms. The new framework is based on a master-worker architecture where each worker runs a parallel program. The parallel implementation allows the sampling to proceed independently on multiple processors, and is demonstrated to scale well to over 100 vertices. It is highly suitable for clusters with an ever increasing number of cores per node. The new method has been applied successfully to the reparameterization of the TIP4P water model, achieving thermodynamic and structural results for liquid water that are as good as or better than the original model, with the advantage of a fully automated parameterization process.
AbstractList This paper proposes a framework and new parallel algorithm for optimization of stochastic functions based on a downhill simplex algorithm. The function to be optimized is assumed to be subject to random noise, the variance of which decreases with sampling time, this is the situation expected for many real-world and simulation applications where results are obtained from sampling, and contain experimental error or random noise. The proposed optimization method is found to be comparable to previous stochastic optimization algorithms. The new framework is based on a master-worker architecture where each worker runs a parallel program. The parallel implementation allows the sampling to proceed independently on multiple processors, and is demonstrated to scale well to over 100 vertices. It is highly suitable for clusters with an ever increasing number of cores per node. The new method has been applied successfully to the reparameterization of the TIP4P water model, achieving thermodynamic and structural results for liquid water that are as good as or better than the original model, with the advantage of a fully automated parameterization process.
Author Stuart, S J
Chahal, D
Trout, C J
Goasguen, S
Author_xml – sequence: 1
  givenname: D
  surname: Chahal
  fullname: Chahal, D
  email: dchahal@clemson.edu
  organization: Sch. of Comput., Clemson Univ., Clemson, SC, USA
– sequence: 2
  givenname: S J
  surname: Stuart
  fullname: Stuart, S J
  email: ss@clemson.edu
  organization: Dept. of Chem., Clemson Univ., Clemson, SC, USA
– sequence: 3
  givenname: S
  surname: Goasguen
  fullname: Goasguen, S
  email: sebgoa@clemson.edu
  organization: Sch. of Comput., Clemson Univ., Clemson, SC, USA
– sequence: 4
  givenname: C J
  surname: Trout
  fullname: Trout, C J
  email: cjtstr@mail.francis.edu
  organization: Dept. of Chem., St. Francis Univ., Loretto, PA, USA
BookMark eNotjMtKw0AYRkdUUGseQNzMA5g612RmWYpVoVIhFRcuyiT5p_0lyYRkCurTWy_f5nDO4rsgJ13ogJArzqacM3sLRYXQVfA6FezQhD4iic0NyzOrlbDaHv86V0IpY43Jzkgyju_sMC3yXJhz8jbbx9C6CPUNfXaDaxpo6KqP2OKXixg6GjwtYqh2boxY0cW-q37ySF9G7LbU0adQo0eoaYFt38AHnTXbMGDctZfk1LtmhOSfE7Je3K3nD-lydf84ny1TtCymUEorVMmqTErQGYPSGJBQg5RSMwYKSmEAvNQgvMuUU8Z75TivOZQMhJyQ679bBIBNP2Drhs-Nzqzkyshvw4VYpg
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/eScienceW.2010.25
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9780769542959
0769542956
EndPage 103
ExternalDocumentID 5693148
Genre orig-research
GroupedDBID 6IE
6IF
6IH
6IK
6IL
6IN
AAJGR
AAWTH
ADFMO
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
IEGSK
IERZE
OCL
RIE
RIL
ID FETCH-LOGICAL-i90t-eb3924b0c633e560eb88e3ede333500e4eb28eef35e2fa64a48ff4a11d1eb0e23
IEDL.DBID RIE
ISBN 9781424489886
1424489881
IngestDate Wed Aug 27 03:14:50 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i90t-eb3924b0c633e560eb88e3ede333500e4eb28eef35e2fa64a48ff4a11d1eb0e23
PageCount 6
ParticipantIDs ieee_primary_5693148
PublicationCentury 2000
PublicationDate 2010-Dec.
PublicationDateYYYYMMDD 2010-12-01
PublicationDate_xml – month: 12
  year: 2010
  text: 2010-Dec.
PublicationDecade 2010
PublicationTitle 2010 Sixth IEEE International Conference on E-Science Workshops
PublicationTitleAbbrev e-sciencew
PublicationYear 2010
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0000527728
ssib015832401
Score 1.4591786
Snippet This paper proposes a framework and new parallel algorithm for optimization of stochastic functions based on a downhill simplex algorithm. The function to be...
SourceID ieee
SourceType Publisher
StartPage 98
SubjectTerms Computational modeling
Noise
Noise measurement
Object oriented modeling
Optimization
parallel optimizaton
Servers
simplex
Stochastic processes
water model
Title Automated, Parallel Optimization of Stochastic Functions Using a Modified Simplex Algorithm
URI https://ieeexplore.ieee.org/document/5693148
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA9zePCksonf5OBxdUnz0fQ4xOFB52ADBx5Gm7y4wrZK7cQ_36Trqgcv3pJAIOTr_V7yfr-H0I0wzGusJEEMIgq4M2lByqwICNeJ0gKUkhVR-DEajdRsFo9bqNdwYQCgCj6DW1-s_vJNrjf-qawvZMwcfN9De1Ekt1yt3d6hQnlpOdq8rxAROuCodlwuFStFdxJPdV3Wv5yUxH2oj9LLNtrLZ87-lW2lMjbDw_8N8wh1f1h7eNzYo2PUgnUHvQ42Ze5QKZgeHieFz5yyxM_unljVBEycWzwpc71IvGIzHjo7V21FXAUT4AQ_5SazDqjiSeaVhL_wYPmWF1m5WHXRdHg_vXsI6oQKQRaTMnB-s_O2UqIlY-CQDqRKAQMDjDFBCHDnZSsAywSENpE84cpanlBqKKQEQnaC2ut8DacISyO0c1QoxNJyZXjqRVVdNy2jFIyyZ6jj52X-vpXMmNdTcv538wU6CJsokUvULosNXKF9_VlmH8V1tc7fS-ymFQ
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4QTfSkBoxve_DISrt90D0SI8EISAKJJB7I7nYqmwBr1sX4822XBT148dY2adL0Nd-0832D0K3QzGmshF4AouVxa9K8iBnhER6HKhaglCyIwr3WYKAmk2BYQY0tFwYAiuAzuHPF4i9fp_HKPZU1hQyYhe87aFdw7pM1W2uze6hQTlyObl9YiPAtdFQbNpcKlKIbkaeyLst_TkqCJpSH6WUd7-VyZ__Kt1KYm87h_wZ6hOo_vD083FqkY1SBZQ29tld5anEp6AYehpnLnTLHz_amWJQUTJwaPMrTeBY6zWbcsZau2Iy4CCfAIe6nOjEWquJR4rSEv3B7_pZmST5b1NG48zC-73plSgUvCUjuWc_Z-lsRiSVjYLEOREoBAw2MMUEIcOtnKwDDBPgmlDzkyhgeUqopRAR8doKqy3QJpwhLLWLrqlAIpOFK88jJqtpusWxFoJU5QzU3L9P3tWjGtJyS87-bb9B-d9zvTXuPg6cLdOBvY0YuUTXPVnCF9uLPPPnIros1_wYgqalc
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2010+Sixth+IEEE+International+Conference+on+E-Science+Workshops&rft.atitle=Automated%2C+Parallel+Optimization+of+Stochastic+Functions+Using+a+Modified+Simplex+Algorithm&rft.au=Chahal%2C+D&rft.au=Stuart%2C+S+J&rft.au=Goasguen%2C+S&rft.au=Trout%2C+C+J&rft.date=2010-12-01&rft.pub=IEEE&rft.isbn=9781424489886&rft.spage=98&rft.epage=103&rft_id=info:doi/10.1109%2FeScienceW.2010.25&rft.externalDocID=5693148
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424489886/lc.gif&client=summon&freeimage=true
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424489886/mc.gif&client=summon&freeimage=true
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781424489886/sc.gif&client=summon&freeimage=true