Multiobjective economic and environmental optimization of global crude oil purchase and sale planning with noncooperative stakeholders. (1st February 2020)
- Record Type:
- Journal Article
- Title:
- Multiobjective economic and environmental optimization of global crude oil purchase and sale planning with noncooperative stakeholders. (1st February 2020)
- Main Title:
- Multiobjective economic and environmental optimization of global crude oil purchase and sale planning with noncooperative stakeholders
- Authors:
- Nicoletti, Jack
You, Fengqi - Abstract:
- Highlights: A multiobjective bilevel mixed-integer optimization framework for oil supply chains. Specific case studies on bilevel optimization of the global crude oil market. Analysis of leader and follower decisions in various scenarios. Comparison of the bilevel problem to deterministic optimization approaches. Abstract: The petrochemical supply chain is a worldwide undertaking, where final products will often travel thousands of miles from oil well to gas station pump. Within the crude oil supply chain, various entities compete and attempt to maximize their profits by exploiting the demands and needs of the other companies within the supply chain. Each company or player in the crude oil industry has its own objective, and it will compete against other players trying to pursue their respective objectives. Due to the non-cooperative structure of the crude oil supply chain, the decisions that maximize profit often do not coincide with decisions that minimize environmental impact, as a reduction in environmental impact usually correlates with a reduction in profit. In this work, the crude oil supply chain from oil well to refinery is modelled as a mixed-integer bilevel linear program that accounts for conflicting objectives and interactions between different stakeholders. The composition, pricing, transportation distances, and environmental impacts of the different crude oils are taken into consideration in the model. In the bilevel problem, the crude oil producers aim toHighlights: A multiobjective bilevel mixed-integer optimization framework for oil supply chains. Specific case studies on bilevel optimization of the global crude oil market. Analysis of leader and follower decisions in various scenarios. Comparison of the bilevel problem to deterministic optimization approaches. Abstract: The petrochemical supply chain is a worldwide undertaking, where final products will often travel thousands of miles from oil well to gas station pump. Within the crude oil supply chain, various entities compete and attempt to maximize their profits by exploiting the demands and needs of the other companies within the supply chain. Each company or player in the crude oil industry has its own objective, and it will compete against other players trying to pursue their respective objectives. Due to the non-cooperative structure of the crude oil supply chain, the decisions that maximize profit often do not coincide with decisions that minimize environmental impact, as a reduction in environmental impact usually correlates with a reduction in profit. In this work, the crude oil supply chain from oil well to refinery is modelled as a mixed-integer bilevel linear program that accounts for conflicting objectives and interactions between different stakeholders. The composition, pricing, transportation distances, and environmental impacts of the different crude oils are taken into consideration in the model. In the bilevel problem, the crude oil producers aim to maximize their own profits from the sale of their crude oil, while the crude oil refiner has the dual objectives of both maximizing the profit made from the sale of distilled products to the market and minimizing the life cycle environmental impact of the refinery products, which is determined by the type of crude oil purchased by the refinery. The resulting model is then applied to two case studies, both based on a U.S. refinery purchasing oil from various crude oil-producing countries. Both case studies produce a set of pareto-optimal decisions for the refiner that display the inherent trade-offs between minimizing "cradle-to-gate" environmental impact and maximizing profit. At the trade-off point in the first case, a 4.4% decrease in profit leads to a 3.0% decrease in the kilograms of CO2 per megajoule of energy produced. Meanwhile, the trade-off point selected in the second case displays a 7.5% reduction in the total environmental impact while decreasing total profit by only 5.9%. Furthermore, the refiner's profit at the trade-off point in the second case is $2.148 M, which is situated between the worst-case deterministic profit of $1.558 M and the best-case deterministic profit of $2.652 M. … (more)
- Is Part Of:
- Applied energy. Volume 259(2020)
- Journal:
- Applied energy
- Issue:
- Volume 259(2020)
- Issue Display:
- Volume 259, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 259
- Issue:
- 2020
- Issue Sort Value:
- 2020-0259-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-02-01
- Subjects:
- Bilevel programming -- Crude oil -- Stackelberg game theory
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2019.114222 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26852.xml