Oil and Gas supply chain optimization using Agent-based modelling (ABM) integration with Big Data technology

Maktoubian, Jamal and Ghasempour-Mouziraji, Mehran and Noori, Mohebollah (2020) Oil and Gas supply chain optimization using Agent-based modelling (ABM) integration with Big Data technology. EAI Endorsed Transactions on Smart Cities, 4 (9): e1. ISSN 2518-3893

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The worldwide oil & gas industry is one of the world's most complex business networks, and is connected with almost every supply chain branch. It includes international and domestic transportation, materials handling, ordering and inventory visibility and control, import/export facilitation and social network, etc. Traditionally, it has been influenced by big oilfield companies. However, in recent years the industry has been changing into a more heterogeneous and diverse network of businesses, and the oilfields are getting smaller and more diverse. One of the reason could be dwindling the oil reserves and growing specialized companies which are able to extract hydrocarbons; another reason is the restructuring and globalization of the entire business as well as some new technology implementing. Using agent-based modeling and big data technology integrity, we are able to optimize supply chain in oil and gas industries.

Item Type: Article
Uncontrolled Keywords: Big Data, Agent-Based Modelling, Oil and Gas Supply Chain
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 09 Sep 2020 11:22
Last Modified: 09 Sep 2020 11:22
URI: https://eprints.eudl.eu/id/eprint/108

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