Abstract
The Brazilian oil industry has gained new momentum after the discovery of large oil reserves in deep under-water. Numerous investments in the oil production chain are expected to support the scale of this operation. Given this context, the use of a decision support system (DSS), which encompasses the complexity of the oil supply chain to support investment decisions, becomes crucial. This paper proposes a DSS that is based on a mixed-integer linear programming (MILP) model that allows the evaluation of different investment alternatives in logistics networks, such as expanding the capacity for transport, handling, and/or storage. Additionally, the DSS is composed of a database structure, business intelligence environment, and graphical visualization tool. The features of the proposed system were evaluated in two case studies. The first case study assesses the synergies between two projects: specifically the expansion of the berthing capacity of vessels in a marine terminal, and the increase in the transport capacity of the pipeline that connects the marine terminal to a distribution base. The second case study evaluates the dependency of the investment in sections of a pipeline that connects a refinery to several distribution bases. These case studies demonstrate the potential use of a DSS that currently optimizes investments in the Brazilian petroleum supply chain.
Fabricio Oliveira
Associate Professor of Operational Research
Fabricio Oliveira is an Associate Professor of Operational Research in the Department of Mathematics and Systems Analysis.