OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

An Agent-Based Decision Support System for Supply Chain Management in the Petroleum Industry

Covaci, Florina Livia and Zaraté, Pascale An Agent-Based Decision Support System for Supply Chain Management in the Petroleum Industry. (2018) In: 4th International Conference on Decision Support Systems Technologies (ICDSST 2018), 22 May 2018 - 25 May 2018 (Heraklion, Greece).

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
498kB

Official URL: https://icdsst2018.files.wordpress.com/2019/03/icdsst2018_short_paper_proceedings.pdf

Abstract

The dynamic economic environment is driving the evolution of traditional supply chains toward a connected, smart, and highly efficient supply chain ecosystem. Algorithms become powerfull tools that enable machines to make autonomous decisions in the digitized supply chain of the future. The integration of software agents with decision support systems provides automated means for decision making. The present paper proposes an agent-based decision support system for supply chain management in the petroleum industry. This industry has a strategic position as it is the base for other essential activities of the economy of any country. The petroleum industry is faced with volatile feedstock costs, cyclical product prices and seasonal final products demand. The current paper considers the position of a refinery as it is at the middle of the integrated petroleum supply chain, between the upstream and downstream. It procures crude oil from upstream assessing the price, quality, timing, and distance to the refinery in order to decide the optimal acquisition. Additionally, the refiner has to carefully monitor the price risk and manage the inventory. The manufacturing activities of the refiner requires thoroughly planning and scheduling the production levels and supply chains for all the derivates and feedstocks for petrochemical industry using tools for decision making in order to estimate market opportunities and threats under volatile market conditions. In order to provide a reliable and practical decision making model, we proposed the integration of supply chain formation algorithm and a mechanism for decision support under uncertainty using maximum expected utility.

Item Type:Conference or Workshop Item (Paper)
Additional Information:ICDSST – PROMETHEE DAYS 2018 on Sustainable Data-Driven & Evidence-based Decision Support with applications to the Environment and Energy sector
HAL Id:hal-02289950
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Universitatea Babes-Bolyai, Cluj-Napoca (ROMANIA)
Laboratory name:
Statistics:download
Deposited On:13 Sep 2019 14:27

Repository Staff Only: item control page