Multi-Objective Mathematical Model for Crude Oil Terminal Scheduling with Tank Farm Operations

Abstract

A critical process underpinning the sustainability of the global economy is the reliable and efficient supply of crude oil from tank farms to international markets. The crude oil terminal serves as the central component of this process. The availability of crude oil in tank farms and the scheduling of oil carriers are key operational decisions made at the oil terminals. This study introduces a novel multi-objective mixed-integer programming (MIP) model for Crude Oil Terminal Scheduling (COTS). The model is an extension of our earlier mathematical modeling framework on COTS. The primary objective of the proposed COTS model is to enhance customer satisfaction by reducing the deviation between actual loading dates and customers’ preferred loading dates. Secondary objectives include managing crude oil inventory levels and reducing the frequency of tank service changes. The model’s results support decision-makers in both scheduling oil carriers and allocating tank storage capacities while enabling dynamic adjustments of tank operations across multiple crude oil types. To address multiple objectives, in this work, several solution approaches, namely the weighted sum (WS) approach, the hierarchical optimization (HO) approach, and the weighted Tchebycheff (WT) approach, are developed. Novel ordering and scaling methods in handling the multiple objectives for COTS using HO and WT are proposed in this paper. The validity of the proposed model and the effectiveness of its solutions are demonstrated through a numerical case study. Based on the numerical analysis, it is estimated that the Pareto-based approaches like HO and WT increase the solution time by ≈400% in the presence of four objectives. However, the Pareto approaches provide a spectrum of operational points to the decision-maker. Finally, key findings and future research paths are discussed.