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QUEUING SIMULATION 509

MANAGEMENT SCIENCE IN ACTION

Petroleum Distribution in the Gulf Of Mexico
omestic suppliers who operate oil refineries tion was used to simulate requests for shipments by
D along the Gulf Coast are helping to satisfy Flor- the petroleum companies. Additional probability dis-
ida’s increasing demand for refined petroleum prod- tributions were used to simulate the travel times
ucts. Barge fleets, operated either by independent depending upon the size and type of barge. Using
shipping companies or by the petroleum companies this information, the simulation model was used to
themselves, are used to transport more than 20 track barge loading times, barge discharge times,
different petroleum products to 15 Florida petroleum barge utilization and total cost.
companies. The petroleum products are loaded at Analysts used simulation runs with a variety of
refineries in Texas, Louisiana and Mississippi and are what-if scenarios to answer questions about the
discharged at tank terminals concentrated in Tampa, petroleum distribution system and to make recom-
Port Everglades and Jacksonville. mendations for improving the efficiency of the oper-
Barges operate under three types of contracts ation. Simulation helped determine the following:
between the fleet operator and the client petroleum
• The optimal trade-off between fleet utilization and
company:
on-time delivery.
• The client assumes total control of a barge and
• The recommended fleet size.
uses it for trips between its own refinery and one
• The recommended barge capacities.
or more discharging ports.
• The best service contract structure to balance the
• The client is guaranteed a certain volume will be
trade-offbetweencustomerserviceanddeliverycost.
moved during the contract period. Schedules vary
considerably depending upon the customer’s Implementation of the simulation-based recommen-
needs and the fleet operator’s capabilities. dations demonstrated a significant improvement in
• The client hires a barge for a single trip. the operation and a significant lowering of petroleum
distribution costs.
A simulation model was developed to analyze the
complex process of operating barge fleets in the Based on E.D. Chajakis, ‘Sophisticated Crude Transportation’, OR/MS
Gulf of Mexico. An appropriate probability distribu- Today (December 1997): 30–34.

12.3 Queuing Simulation

The simulation models discussed thus far have been based on independent trials in
which the results for one trial do not affect what happens in subsequent trials. In this
sense, the system being modelled does not change or evolve over time. Simulation
models such as these are referred to as static simulation models. In this section, we
develop a simulation model of a queuing system where the state of the system,
including the number of customers in the queue and whether the service facility is
busy or idle, changes or evolves over time. To incorporate time into the simulation
model, we use a simulation clock to record the time that each customer arrives for
service as well as the time that each customer completes service. Simulation models
that must take into account how the system changes or evolves over time are
referred to as dynamic simulation models. In situations where the arrivals and
departures of customers are events that occur at discrete points in time, the simu-
lation model is also referred to as a discrete-event simulation model.

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