A MILP-based clustering strategy for integrating the operational management of crude oil supply
Title
A MILP-based clustering strategy for integrating the operational management of crude oil supply
Subject
Bilinear terms
Blending
Clustering
Crude oil supply
MILP
crude oil
Description
In this paper, we present a MILP clustering formulation for tackling the operational management of crude oil supply (OMCOS) proposed by de Assis et al. (2019). The OMCOS consists of defining the scheduling of vessel trips between offshore platforms and a crude oil terminal, combined with the scheduling of operations in a terminal to supply crude oil to distillation columns. The benefits of using the clustering solution as a pre-step before solving the OMCOS are: (a) reduces the number of routes for vessels
(b) simplifies offloading and unloading operations
(c) imposes rules for crude mixtures in clusters of storage tanks that minimize property variations
and (d) produces bounds on crude properties inside storage tanks that are used to linearize bilinear terms in blending constraints. Through the combination of clusters and a MILP-NLP decomposition, near optimal solutions were obtained for a set of representative instances of OMCOS at a reduced computational cost.
Publisher
Computers & Chemical Engineering
Date
2021-02-01
Contributor
Assis, Leonardo S.
Camponogara, Eduardo
Grossmann, Ignacio E.
Type
Journal Article
Identifier
2RJTDKLS
0098-1354
10.1016/j.compchemeng.2020.107161
Collection
Citation
“A MILP-based clustering strategy for integrating the operational management of crude oil supply,” Lamar University Midstream Center Research, accessed May 15, 2024, https://lumc.omeka.net/items/show/1406.