Stochastic analysis of crude oil procurement and processing under uncertain demand for bunker fuel oil

Abstract

Bunker fuel oil (ifo), one of the products of petroleum refining, has a strong impact in the production process because it drives the availability of heavy residues that depend on the crude quality. A simplified stochastic model for the Administracio´n Nacional de Combustibles Alcohol y Portland refinery, based on the uncertainty of the demand for ifo, is proposed for comparison with the current approach of deterministic demand. In this model, the benefits of the production process are maximized, taking decisions on the more suitable raw material, intermediate products and final blends in order to fulfill quality and demand requirements of final products. A specific case is analyzed where the maximum benefit is achieved when the most expensive crude quality is purchased, due to a lack of incentive to produce extra amounts of heavy fuel oil that must be exported at a non-attractive price. Results are compared with the solution of a deterministic model with mean demand. In addition, the stochastic model solution depicts how the refinery should operate for each scenario of ifo demand.

Procurement risk management under uncertainty: a review

“…For one-stage decision making, it is often the case that buyer needs to design the procurement plan such as supply base configuration, lot sizing and forward contract selection before the demand is realized (e.g. Swaminathan and Shanthikumar, 1999; Zimberg and Testuri, 2006). While two-stage decision-making process divides the single period into two stages: the first stage is similar as one-stage model, and the second stage tries to figure out how many products need to be bought from spot market or via instance order after obtaining more accurate demand information (e.g.…”

Joint optimization of pricing and planning decisions in divergent supply chain

“…After this process, raw materials result in more than one component, according to a conversion factor defined as the amount of component b generated from processing one unit of raw material i . The use of such conversion factors is common in optimization models for supply chain planning involving natural resources, such as copper (Epstein et al., ) and oil (Kong, ; Zimberg and Testuri, ).…”

Short‐term crude oil scheduling with preventive maintenance operations: a fuzzy stochastic programming approach

“…(), in which the short‐term crude oil scheduling problem was studied considering unavailability periods for the charging tanks in an uncertain environment, this work investigates the integrated oil production planning and scheduling problem considering uncertainty of main parameters including demand and availability constraints for the maintenance operations. As reported by Zimberg and Testuri (), the crude oil scheduling problem normally takes place in a highly uncertain environment in the real‐world setting. Thus, this study considers that the failure happens in an environment imposed to uncertainty.…”