Continuous‐time scheduling formulation for straight pipelines

Abstract

Pipelines represent the most cost‐effective way of transporting large quantities of refined petroleum products over large distances but can be challenging to operate. In this article, we propose a new mixed‐integer linear programming formulation for scheduling straight pipelines with multiple single and dual purpose nodes. The model allows for simultaneous injections and deliveries, and interacting pumping runs, in which a segment of the pipeline simultaneously receives material from its refinery and upstream segment. In contrast to previous batch centric models, it uses segment dependent coordinates. To make it efficient by design, we rely on generalized disjunctive programming and develop disjunctions for which the convex hull reformulation is simple (roughly the same number of variables and constraints as its big‐M counterpart). Through the solution of a set of test cases from the literature, we show a better utilization of the pipeline capacity that is translated into a lower makespan. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1923–1936, 2017

Scope for optimal Scheduling of Multiproduct Pipelines with Multi-batch Sequential transportation

“…In addition, the GDP model can use logical reasoning to eliminate the unfeasible solution domain, reduce the searching space, and improve the solution efficiency [41]. Mostafaei and Castro [22] relied on GDP to propose a continuous-time model for the detailed scheduling of multi-source and multi-sink pipelines, significantly improving the utilization rate of pipelines and shortening the make span. They inserted a number of empty batches to define new batches injected by the intermediate injection stations, resulting in a sharp increase in model size.…”

“…Hence Castro and Mostafaei [3] extended their work a product-centric model based on GDP. Compared with a product-centric formulation based on the Resource-Task Network (RTN) [22], the new GDP-based one only needs roughly one quarter of the binary variables for the same linear relaxation, greatly reducing model scale and improving solving efficiency.…”

Optimal Economic Operation of Liquid Petroleum Products Pipeline Systems

“…Contemporary studies typically seek to minimize the energy used for pumping and incorporate engineering models of varying fidelity [34,60]. A variety of studies have examined time-dependent scheduling of single commodity transport [40,72,7,44], various network topologies (i.e. single-and multi-source) [7,8], and optimization under uncertainty [42].…”

Continuous‐time scheduling formulation for multipurpose batch plants

“…In contrast, in ‐ continuous‐time representations the length of time slots is selected by the optimization, thus leading to a significant reduction in the number of decision variables. Though continuous‐time approaches will result in better solutions than their discrete counterparts, they inevitably need tuning parameters (e.g., number of time slots), thus requiring an iterative procedure to find the optimal solutions . This is a big drawback because the initial guess on the minimum number of time slots is hardly trivial, thus involving, in most cases, solving a particular instance at least five times (see, e.g., Table in Reference ).…”