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A Mixed-Integer Optimization Strategy for Oil Supply in Distribution Complexes

为在分发建筑群的油供应的混合整数优化策略

作     者:Mas, Rodrigo Pinto, Jose M. 

作者机构:Univ Sao Paulo Dept Chem Engn BR-05508900 Sao Paulo Brazil 

出 版 物:《OPTIMIZATION AND ENGINEERING》 (最优化与工程学)

年 卷 期:2003年第4卷第1-2期

页      面:23-64页

核心收录:

学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0701[理学-数学] 

主  题:mixed integer optimization pipeline transportation scheduling crude oil 

摘      要:As a result of an increasingly competitive market, companies must find ways to organize their activities regarding their economic outcome. An important feature in this context involves transportation operations, usually considered one of the major bottlenecks in the production chain. While delays imply loss of time and lack of resources, deliveries ahead of the deadlines may cause excess of inventories. Therefore, every company must pursue efficient transportation schedules within their operational planning. This work addresses short-term crude oil scheduling problems in a distribution complex that contains ports, refineries and a pipeline infrastructure capable of transferring oil from the former to the latter. The ports comprise piers, which receive vessels for discharging, storage tanks and a network that connects each other. The refineries have their own storage infrastructure, modeled as a large storage unit, along with crude distillation units, considered as constant level consumers. The problem involves a number of other issues, including intermediate storage, settling tasks and allocation of crude oil by its qualitative characteristics. A decomposition strategy based on large-scale mixed-integer linear programming (MILP) continuous-time models is developed. First, an MILP model that considers an aggregate representation for the pipeline and intermediate storage infrastructure is proposed. Decision variables involve the assignment of oil tankers to piers as well as tanker unloading and pipeline loading operations. The solution of this model provides the initial conditions for MILP models that represent the pipeline and intermediate storage infrastructure at a detailed level. Algorithms based on the LP-based branch-and-bound method are employed. Results from a port scenario of 13 tankers, 4 piers, 14 crude types, 18 storage tanks and 2 pipelines were obtained in approximately 90 minutes from an MILP problem containing 1996 continuous variables, 1039 binary var

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