Imperial College London
Alternate

ProfessorWilliamKnottenbelt

Faculty of Engineering, Department of Computing

Professor of Applied Quantitative Analysis
 
 
 
//

Contact

 

+44 (0)20 7594 8331w.knottenbelt Website

 
 
//

Location

 

E363ACE ExtensionSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Pesu:2017:10.4108/eai.25-10-2016.2267060,
author = {Pesu, T and Knottenbelt, WJ},
doi = {10.4108/eai.25-10-2016.2267060},
pages = {133--136},
publisher = {EAI},
title = {Optimising hidden stochastic PERT networks},
url = {http://dx.doi.org/10.4108/eai.25-10-2016.2267060},
year = {2017}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - This paper introduces a technique for minimising subtask dispersion in hidden stochastic PERT networks. The technique improves on existing research in two ways. Firstly, it enables subtask dispersion reduction in DAG structures, whereas previous techniques have only been applicable to single-layer split-merge or fork-join systems. Secondly, the exact distributions of subtask processing times do not need to be known, so long as there is some means of generating samples. The technique is further extended to use a metric which trades off subtask dispersion and task response time.
AU  - Pesu,T
AU  - Knottenbelt,WJ
DO  - 10.4108/eai.25-10-2016.2267060
EP  - 136
PB  - EAI
PY  - 2017///
SP  - 133
TI  - Optimising hidden stochastic PERT networks
UR  - http://dx.doi.org/10.4108/eai.25-10-2016.2267060
UR  - http://hdl.handle.net/10044/1/53026
ER  -
Download