About: Optimal computing budget allocation     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.org associated with source document(s)
QRcode icon
http://dbpedia.org/describe/?url=http%3A%2F%2Fdbpedia.org%2Fresource%2FOptimal_computing_budget_allocation

In computer science, optimal computing budget allocation (OCBA) is an approach to maximize the overall simulation efficiency for finding an optimal decision. It was introduced in the mid-1990s by Dr. Chun-Hung Chen. OCBA determines the number of replications or the simulation time that is needed in order to receive acceptable or best results within a set of given parameters. This is accomplished by using an asymptotic framework to analyze the structure of the optimal allocation.

AttributesValues
rdfs:label
  • Optimal computing budget allocation (en)
  • 最优计算量分配 (zh)
rdfs:comment
  • 最优计算量分配(OCBA) 是最早由陈俊宏教授于90年代中期提出的一个概念。这一方法试图在找到一个最优决策的前提下最大化仿真效率。 简言之,OCBA是一种仿真方法,它能够在给定一组仿真参数的情况下,帮助确定所需的仿真次数及(或)所需的仿真时间,以达到可接受的(或最好的)结果。 其具体做法是通过使用一个渐进框架对最优分配的结构进行分析。 (zh)
  • In computer science, optimal computing budget allocation (OCBA) is an approach to maximize the overall simulation efficiency for finding an optimal decision. It was introduced in the mid-1990s by Dr. Chun-Hung Chen. OCBA determines the number of replications or the simulation time that is needed in order to receive acceptable or best results within a set of given parameters. This is accomplished by using an asymptotic framework to analyze the structure of the optimal allocation. (en)
foaf:depiction
  • http://commons.wikimedia.org/wiki/Special:FilePath/Comparing_5_different_alternatives_with_respect_to_Cost.png
dcterms:subject
Wikipage page ID
Wikipage revision ID
Link from a Wikipage to another Wikipage
Link from a Wikipage to an external page
sameAs
dbp:wikiPageUsesTemplate
thumbnail
has abstract
  • In computer science, optimal computing budget allocation (OCBA) is an approach to maximize the overall simulation efficiency for finding an optimal decision. It was introduced in the mid-1990s by Dr. Chun-Hung Chen. OCBA determines the number of replications or the simulation time that is needed in order to receive acceptable or best results within a set of given parameters. This is accomplished by using an asymptotic framework to analyze the structure of the optimal allocation. OCBA has also been shown effective in enhancing partition-based random search algorithms for solving deterministic global optimization problems. (en)
  • 最优计算量分配(OCBA) 是最早由陈俊宏教授于90年代中期提出的一个概念。这一方法试图在找到一个最优决策的前提下最大化仿真效率。 简言之,OCBA是一种仿真方法,它能够在给定一组仿真参数的情况下,帮助确定所需的仿真次数及(或)所需的仿真时间,以达到可接受的(或最好的)结果。 其具体做法是通过使用一个渐进框架对最优分配的结构进行分析。 (zh)
gold:hypernym
prov:wasDerivedFrom
page length (characters) of wiki page
foaf:isPrimaryTopicOf
is Link from a Wikipage to another Wikipage of
is Wikipage redirect of
is foaf:primaryTopic of
Faceted Search & Find service v1.17_git139 as of Feb 29 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 08.03.3332 as of Feb 27 2025, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (61 GB total memory, 60 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software