A Robust Event-Based Continuous Time Formulation for Tank Transfer Scheduling

Abstract

A generalized model is proposed for the continuous time scheduling problem of fluid transfer in tanks. This model generally and more robustly handles the synchronization of time events with material balances than previous proposed models in the literature. A novel method for representing the flow to and from a tank is developed with the potential for significant reduction in the number of necessary time events required for continuous time scheduling formulations. The problem involves the optimal operation of fluid transfer from input sources to tanks, transfer between the tanks, and the transfer from tanks to output destinations. An efficient mixed-integer nonlinear programming formulation is developed based on continuous representation of time domain under the assumption of no simultaneous input and output flow to a tank for fluid streams comprised of multiple components. The new modeling paradigm is applied to examples from the literature for developing refinery crude unit charging schedules.

New MINLP formulation for the multiperiod pooling problem

“…We now move away from the Resource-Task Network 23 nomenclature to present a model that is easier to understand, something that is possible due to the discrete-time nature of the current problem, with time periods that are known a priori (for a review of the alternative time representation concepts see Harjunkoski et al 40 ). Motivated by the need to avoid numerical irregularities, Furman et al 18 were the firsts to relate the remaining content of a tank with its outlet streams through a nonlinear constraint, an approach that continued in subsequent work. 20,41 However, these works did not explicitly define a split fraction variable and used individual flows, total flows, and tank volumes, leading to the appearance of more bilinear terms.…”

A Mixed-Integer Linear Programming Model for Optimizing the Scheduling and Assignment of Tank Farm Operations

“…Yet another type of continuous time models relevant to the TFOP comes from the study of tank transfer and crude oil scheduling problems in the refining industry (Furman et al, 2007;Mouret et al, 2009;Mouret et al, 2011 ). Among these alternative models, we use the Multi-operation Sequencing (MOS) model described by Mouret et.…”

A novel transition identification mechanism for the diesel blending and distribution scheduling problem using the discrete time representation with two time-scales granularity

“…In the last two decades, a lot of attention has been devoted to studying the crude oil supply operation since it is an important activity that can affect directly the entire refinery operation. The reported literature has comprised a gamut of subjects, covering aspects related to problem features (different topologies, restrictive operating rules, and volume decisions), time representation, model tightness and solution strategies (Shah, 1996;Pinto et al, 2000;Moro and Pinto, 2004;Furman et al 2007;Saharidis and Ierapetritou, 2009;Mouret et al 2011;Chen et al 2012).…”