Efficient Tool for the Scheduling of Multiproduct Pipelines and Terminal Operations
This paper addresses the problem of scheduling a transmission pipeline carrying several petroleum products from a single oil refinery to a unique distribution center over a monthly horizon. The proposed approach is based on a very efficient MILP continuous-time formulation that is capable of determi...
| Autores: | , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2008 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/24870 |
| Acesso em linha: | http://hdl.handle.net/11336/24870 |
| Access Level: | acceso abierto |
| Palavra-chave: | Refined Products Pipelines Pipeline Terminal Operations Scheduling Optimization Approach https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Resumo: | This paper addresses the problem of scheduling a transmission pipeline carrying several petroleum products from a single oil refinery to a unique distribution center over a monthly horizon. The proposed approach is based on a very efficient MILP continuous-time formulation that is capable of determining the optimal pipeline batch sequence and lot sizes as well as the schedule of lot injections in the line and the timing of product deliveries to the distribution terminal. Moreover, the MILP model rigorously accounts for customer product demands on a daily basis, key terminal operations like lot settling periods for quality control tasks and a predefined set of alternative lot sizes to get a better control of tank availability. The approach neither requires to divide pipeline segments into a number of single-product packs of known capacities since the volume scale is also handled in a continuous manner. Results found for several examples involving the schedule of a real-world single-source single-destination multiproduct pipeline under different operational scenarios show that the proposed method leads to better pipeline schedules than previous approaches in a more rigorous way and at much lower computational cost. |
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