Application Case

Optimal Transport for ExxonMobil Downstream Through a DSS

ExxonMobil, a petroleum and natural gas company, operates in several countries

worldwide. It provides several ranges of petroleum products including clean fuels,

lubricants, and high$-$value products and feedstock to several customers. This is

completed through a complex supply chain between its refineries and customers.

One of the main products ExxonMobil transports is vacuum gas oil $($VGO$).$

ExxonMobil transports several shiploads of vacuum gas oil from Europe to the

United States. In a year, it is estimated that ExxonMobil transports about $60-70$

ships of VGO across the Atlantic Ocean. Hitherto, both ExxonMobil$-$managed vessels and third$-$party vessels were scheduled to transport VGO across the Atlantic through a cumbersome manual process. The whole process required the collaboration of several individuals across the supply chain organization. Several customized spreadsheets with special constraints, requirements, and economic trade$-$offs were used to determine the transportation schedule of the vessels. Some of the constraints included:

$1.$ Constantly varying production and demand projections

$2.$ Maximum and minimum inventory constraints

$3.$ A pool of heterogeneous vessels $($e$.$g$.,$ ships with varying speed, cargo size$)$

$4.$ Vessels that load and discharge at multiple ports

$5.$ Both ExxonMobil$-$managed and third$-$party sup$-$ plies and ports

$6.$ Complex transportation cost that includes variable overage and demurrage costs

$7.$ Vessel size and draft limits for different ports

The manual process could not determine the actual routes of vessels, the timing of

each vessel, and the quantity of VGO loaded and discharged. Additionally,

consideration of the production and consumption data at several locations rendered the manual process burdensome and inefficient.

Methodology$/$Solution

A decision support tool that supported schedulers in planning an optimal schedule

for ships to load, transport, and discharge VGO to and from multiple locations was

developed. The problem was formulated as a mixed$-$integer linear programming

problem. The solution had to satisfy requirements for routing, transportation,

scheduling, and inventory management vis$-$a$-$vis varying production and demand

profiles. A mathematical programming language, GAMS, was used for the problem

formulation and Microsoft Excel was used as the user interface. When the solver

$($ILOG CPLEX$)$ is run, an optimal soluton is reached at a point when the objectve

value of the incumbent solution stops improving. This stopping criterion is determined by the user during each program run.

Results$/$Benefits

It was expected that using the optimizaton model will lead to reduced shipping cost

and less demurrage expenses. These would be achieved because the tool would be

able to support higher utilization of ships and help make ship selecton $($e$.$g$.,$

Panamax versus Aframax$)$ and design more optimal routing schedules. The

researchers expected to extend the research by exploring other alternate

mathematical methods to solve the scheduling problem. They also intended to give

the DSS tool the capability to consider multiple products for a pool of vessels.

Source: K$.$ C$.$ Furman, $].$ H$.$ Song, G$.$ R$.$ Kocis, M$.$ K$.$ McDonald, and P$.$ H$.$ Warrick, "Feedstock Routing in the ExxonMobil Downstream Sector," Interfaces, Vol. $41,$ No$.2,2011,$ pp$.149-163.$

DISCUSSION QUESTIONS

$1.$ List three ways in which manual scheduling of ships could result in more

operatonal cost as compared to the tool developed.

$2.$ In what other ways can ExxonMobil leverage the decision support tool developed to expand and optimize their other business operatons?

$3.$ What are some strategic decisions that could be made by decision makers using the tool developed.

$4.$ Consider the environmental impacts associated with maritime transport of oil products. How could the DSS be modified or used to minimize environmental risks and align with global sustainability efforts?

$5.$ From the ExxonMobil case, what do you see as the key challenges and benefits of using decision support systems in traditional industries like oil and gas? Share your thoughts.

Submission Instructions:

Please submit your responses in a single document & Ensure that your answers are clearly numbered and thoroughly address each question.