Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap

The P-graph framework is a combinatorial approach to synthesising and optimising process networks. It is very efficient in handling problems with high combinatorial complexity and has shown great superiority in reducing the related computational burden. Over the years, it has proven its efficiency i...

Full description

Bibliographic Details
Main Authors: P.S. Varbanov, F. Friedler, J.J. Klemes
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2017-10-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/309
id doaj-46ef51ec4c1541dbb105fba5ae8ac7a0
record_format Article
spelling doaj-46ef51ec4c1541dbb105fba5ae8ac7a02021-02-17T21:21:52ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162017-10-016110.3303/CET1761256Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap P.S. VarbanovF. FriedlerJ.J. KlemesThe P-graph framework is a combinatorial approach to synthesising and optimising process networks. It is very efficient in handling problems with high combinatorial complexity and has shown great superiority in reducing the related computational burden. Over the years, it has proven its efficiency in solving topologically and combinatorically challenging problems. Many successful applications to scientific and real-life problems have been produced, demonstrating the benefit potential. The application areas range from the initial chemical process synthesis to identifying the mechanisms of chemical and biochemical reactions, supply chains optimisation, regional resource planning, crisis management, evacuation planning and business process modelling. There have been tools of several generations implementing the P-graph framework, with a simple user interface, but featuring serious data input requirement. The P-graph framework also allows sensitivity analysis and produces usually a set of recommended solutions as opposed to the usual single output from straight applications of MP. The current contribution makes a critical overview of the achievements from applying the P-graph framework and the main issues to be dealt with. Based on that, a set of recommendations is made on the necessary future development of the implementations regarding modelling capability, data and algorithmic interfaces, representation of the modelled networks, as well as complexity management. https://www.cetjournal.it/index.php/cet/article/view/309
collection DOAJ
language English
format Article
sources DOAJ
author P.S. Varbanov
F. Friedler
J.J. Klemes
spellingShingle P.S. Varbanov
F. Friedler
J.J. Klemes
Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
Chemical Engineering Transactions
author_facet P.S. Varbanov
F. Friedler
J.J. Klemes
author_sort P.S. Varbanov
title Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
title_short Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
title_full Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
title_fullStr Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
title_full_unstemmed Process Network Design and Optimisation Using P-graph: The Success, the Challenges and Potential Roadmap
title_sort process network design and optimisation using p-graph: the success, the challenges and potential roadmap
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2017-10-01
description The P-graph framework is a combinatorial approach to synthesising and optimising process networks. It is very efficient in handling problems with high combinatorial complexity and has shown great superiority in reducing the related computational burden. Over the years, it has proven its efficiency in solving topologically and combinatorically challenging problems. Many successful applications to scientific and real-life problems have been produced, demonstrating the benefit potential. The application areas range from the initial chemical process synthesis to identifying the mechanisms of chemical and biochemical reactions, supply chains optimisation, regional resource planning, crisis management, evacuation planning and business process modelling. There have been tools of several generations implementing the P-graph framework, with a simple user interface, but featuring serious data input requirement. The P-graph framework also allows sensitivity analysis and produces usually a set of recommended solutions as opposed to the usual single output from straight applications of MP. The current contribution makes a critical overview of the achievements from applying the P-graph framework and the main issues to be dealt with. Based on that, a set of recommendations is made on the necessary future development of the implementations regarding modelling capability, data and algorithmic interfaces, representation of the modelled networks, as well as complexity management.
url https://www.cetjournal.it/index.php/cet/article/view/309
work_keys_str_mv AT psvarbanov processnetworkdesignandoptimisationusingpgraphthesuccessthechallengesandpotentialroadmap
AT ffriedler processnetworkdesignandoptimisationusingpgraphthesuccessthechallengesandpotentialroadmap
AT jjklemes processnetworkdesignandoptimisationusingpgraphthesuccessthechallengesandpotentialroadmap
_version_ 1724264253040361472