An optimization framework for scheduling multi-period multi-product oil pipeline systems under belief degree-based uncertain parameters

Considering that one of the most significant challenges for oil industry planners is developing an effective schedule plan that reduces costs, increases profitability, and enhances customer satisfaction, this article improves a formulation for scheduling multi-product pipelines. The primary goal is to minimize operational expenses, which include inventory and shortages, interfaces, and labor. Consideration is given to batch sizing limits, inventory carrying costs, backlog, and settlement periods. Additionally, certain parameters have been classified as having the belief degree-based type of uncertainty due to a lack of relevant historical data. As solution strategies, three separate conversion approaches are used. The model's efficiency and dependability, as well as the proposed methodologies, are demonstrated numerically. Sensitivity analysis shows that objective function values are highly dependent on changes in confidence levels, so the best technique is implemented.

Automated summary

This article improves a formulation for scheduling multi-product pipelines in order to minimize operational expenses. It considers factors such as batch sizing limits and inventory carrying costs, and proposes three solution strategies. Numerical demonstrations are used to showcase the efficiency and dependability of the model.