Stochastic Modeling Approach for Downstream Oil Supply Chain

Lima, Camilo; Relvas, Susana; Barbosa‐Póvoa, Ana Paula

doi:10.1016/b978-0-444-63965-3.50225-7

Cited by 3 publications

(5 citation statements)

References 3 publications

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“…This method leads to an uncontrollable and large optimization problem, and as a result, reduction algorithms are used to reduce the scale of the problem, which are better than deterministic and stochastic algorithms. [13] In 2008, Kaufmann et al corrected horizontal and vertical transmissions in the US oil supply chain by satisfying the vector error correction models of the oil price. To examine the direction of horizontal and vertical transmissions in the oil supply chain, vector error correction is examined, which includes six variables: 1) crude oil price 2) US refinery productivity rate 3) US crude oil reserves 4) US gasoline reserves 5) US gasoline prices and 6) fuel prices.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this equation 𝜃 0 ,𝑑 shows the effect of each pollutant unit p emitted on p damage d. Equation ( 12) shows inventory of pollutants, which is the sum of the amount of pollutants emitted. Equation (13) to Equation (18) show the amount of fluids sent from the supplier to the Miandoab warehouse and from the warehouse to the consumers must be between the upper and lower bounds of the capacity of the pipeline and oil tanker vehicles. Equation (19) to Equation (25) shows the variability of demand for petroleum products at the upper and lower bounds.…”

Section: Definition Of Objective Functions and Constraintsmentioning

confidence: 99%

“…Figure 10 Variable output of sending petroleum products from Miandoab city to cities by oil tanker (Figure 10 and table 13 ) shows the amount of one of the oil products sent by 4 oil tankers from 3 oil tanks to one of the stations during 10 periods.…”

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confidence: 99%

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A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

Attaria,

Ejlaly,

Ghahvechia

2023

Preprint

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The oil industry plays an important role in global energy demand. Oil and other fossil fuels have been a major cause of environmental and global warming for decades. Many industries need oil as a major energy source, and it is important to minimize the environmental impact of oil( minimizing greenhouse gas (GHG)) and maximize its benefits Petroleum Revenue Management Act (PRMA). The environmental impact of the oil industry is the emission of gases such as carbon dioxide, sulfur dioxide, and nitrogen oxide, which directly and indirectly affect the environment.So it is important, creating a green supply chain network(GSCN) model that pursues several goals.This study presents a multi-objective optimization model for energy allocation and petroleum product distribution in green supply chains.For this purpose a multi-objective mixed-integer programming (MIP) model is formulated to develop. The proposed model is designed a green supply chain(GSC) to reduce oil company costs and greenhouse gas(GHG) emissions under uncertain demand. We solve the proposed model with GAMS and present a case study to IRAN National Petroleum Corporation(INPC) MIANDOAB demonstrate the applicability and exhibit efficacy of the proposed model.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Definition Of Objective Functions and Constraintsmentioning

confidence: 99%

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A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

Attaria,

Ejlaly,

Ghahvechia

2023

Preprint

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“…, 2013; Oliveira and Hamacher, 2012a; Fernandes et al. , 2017; Lima et al. , 2017, 2018a; Oliveira et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The most important studies in the petroleum supply chain field such as different linear planning models (Fernandes et al, 2013;Gao, 2018) random linear planning models in petroleum product supply chain strategic, operational and tactical planning (Al-Othman et al, 2008;MirHassani, 2008;Ribas et al, 2010;MirHassani and Noori, 2011;Tong et al, 2012;Leiras et al, 2013;Oliveira et al, 2013;Oliveira and Hamacher, 2012a;Fernandes et al, 2017;Lima et al, 2017Lima et al, , 2018aOliveira et al, 2014) linear/non-linear complex integer planning (Guajardo et al, 2013;Kuo and Chang, 2008;Pinto et al, 2000;Neiro and Pinto, 2004), fuzzy linear planning (Ghatee and Hashemi, 2009), robust planning (Lima et al, 2018b(Lima et al, , 2019, twolevel planning (Gao and You, 2019;Zang et al, 2020;Oliveira and Hamacher, 2012b) and multi-objective planning (Gholami et al, 2019). As visible, these planning models lack multiobjective functions.…”

Section: Literature Reviewmentioning

confidence: 99%

A mathematical tri-level programming model for designing an integrated dynamic petroleum product supply chain

Ahwazian

Amindoust

Tavakkoli–Moghaddam

et al. 2022

JAMR

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PurposeThe purpose of this paper is to design petroleum products’ supply chain management, which includes efficient integration of suppliers, manufacturers, storehouses and retailers.Design/methodology/approachThis paper proposes that a three-level supply chain will be turned into a bi-level supply chain of petroleum products by simultaneous integration of the middle level with the upstream and downstream levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels.FindingsThe concepts of the design, structure and outputs are led by the model's solution. The model also responds to the variations in the market via coordination in the related decisions to the distribution, production and inventory issues, and also coordinating between the demands and production.Research limitations/implicationsThis paper has limited its analysis to definite values due to the over-expansion of calculations and analysis. Future works can study other aspects of the proposed model for a multi-level petroleum product supply chain in different states of certain parameters and time zones.Practical implicationsThe designed model can directly and transparently help the oil managers and decision-makers lower the costs of manufacturing, distribution and sales with respect to the determined criteria.Originality/valueThis paper establishes that effectiveness of the dynamic petroleum materials supply chain design will increase by considering maintained and increased production costs and coordinate management flows at all levels by supply chain creation’s integration.

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Design of a sustainable integrated crude oil manufacturing network with risk cover and uncertainty considerations: a case study

Azarakhsh

Sahebi

Hosseini

2021

J Ambient Intell Human Comput

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Stochastic Modeling Approach for Downstream Oil Supply Chain

Cited by 3 publications

References 3 publications

A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

A mathematical tri-level programming model for designing an integrated dynamic petroleum product supply chain

Design of a sustainable integrated crude oil manufacturing network with risk cover and uncertainty considerations: a case study

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