.png){kind=icon}
.png){kind=icon}
Return
An effective decomposition algorithm for scheduling branched multiproduct pipelines
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compchemeng.2021.107494.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article develops a novel two-stage algorithm for the detailed scheduling of branched multiproduct pipeline systems with a single refinery and multiple depots. It features continuous-time models allowing multiple batches to be injected/delivered over a slot. The first-stage model reduces the complexity by neglecting the lower flowrate limits, enforced by big-M constraints. The objective is to minimize the makespan. The second-stage model works with the first-stage assignments and with an extended time grid. Coupled with a backtracking mechanism, the proposed algorithm can significantly reduce computational time and improve the pipeline transportation capacity. We use four benchmark instances from the literature to test and validate the effectiveness and superiority of the method proposed in this paper. Compared to the literature, a new optimal solution is reported in one case, while the computational time is reduced by at least one order of magnitude in the other cases. (c) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Optimization
Mixed-integer linear programming
Continuous-time formulation
Branched pipeline networks
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
3.9
Papers:
8.1K
Citations:
1.7W