Evolutionary multi-objective optimization of environmental indicators of integrated crude oil supply chain under uncertainty

This study presents a multi-objective mathematical model for integrating upstream and midstream segments of crude oil supply chain in the context of environmental indicators. An actual case study in the Persian Gulf is considered. Upstream and midstream segments are integrated into the presented mod...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of cleaner production Jg. 152; S. 295 - 311
Hauptverfasser:	Azadeh, Ali, Shafiee, Farideh, Yazdanparast, Reza, Heydari, Jafar, Fathabad, Abolhassan Mohammadi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 20.05.2017
Schlagworte:	algorithms case studies environmental indicators Environmental issues mathematical models Multi-objective evolutionary algorithm based on decomposition (MOEA-D) Multi-objective particle swarm optimization (MOPSO) Non-dominated sorting genetic algorithm (NSGA-II) oil fields Oil supply chain Persian Gulf petroleum planning supply chain uncertainty Persian Gulf Multi-objective particle swarm optimization (MOPSO) Non-dominated sorting genetic algorithm (NSGA-II) Multi-objective evolutionary algorithm based on decomposition (MOEA-D) Oil supply chain Environmental issues
ISSN:	0959-6526, 1879-1786
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!