1.1 Opetation research is used to
solve organization's problems
1.1.1 1
1.1.1.1 Formulate the problem
1.1.1.1.1 Define the problem
1.1.1.1.1.1 Organization objectives
1.1.1.1.1.2 parts of the organization must be
studied before the problem can
be solved
1.1.2 2
1.1.2.1 observe the system
1.1.2.1.1 collect's data
1.1.2.1.1.1 stimates values and parameters
1.1.2.1.1.2 affect organizations plorbems
1.1.3 3
1.1.3.1 Formulate a mathematical model of the problem
1.1.3.1.1 Many mathematicla techniques that can be used to model systems
1.1.4 4
1.1.4.1 Verify the Model and Use the Model for Prediction
1.1.4.1.1 The operations researcher now tries to determine if the mathematical model
developed in step 3 is an accurate representation of reality.
1.1.4.1.1.1 check and see if (1) accurately represents yield for values of the decision variables
that were not used to estimate (1).
1.1.4.1.1.1.1 then we might have to add new constraints to our model, and
the yield of the process [and Equation (1)] might change.
1.1.5 5
1.1.5.1 Select a Suitable Alternative
1.1.5.1.1 s, the operations researcher now chooses the alternative that best meets the
organization’s objectives.
1.1.6 6
1.1.6.1 Present the Results and Conclusion of the Study to the Organization
1.1.6.1.1 After presenting the results 1.2 The Seven-Step
Model-Building Process 5 of the operations
research study
1.1.6.1.1.1 This may result from incorrect definition of the organization’s problems or
from failure to involve the decision maker from the start of the project
1.1.6.1.1.1.1 return to stps
1,2,3
1.1.7 7
1.1.7.1 Implement and Evaluate Recommendations
1.1.7.1.1 The analyst aids in implementing the recommendations
and the system must be constantly monitored
2 CITGO Petroleum
2.1 Optimizing Refinery Operations
2.1.1 1
2.1.1.1 Minimize the cost of operating CITGO’s refineries.
2.1.2 2
2.1.2.1 The Lake Charles, Louisiana, refinery
2.1.2.1.1 1. Cost of producing each of CITGO’s products
depends on the inputs used to produce each
product
2.1.2.1.2 2. Installation of a new
metering system.
2.1.2.1.3 3.The yield associated with each input–output
combination
2.1.2.1.4 4.To reduce maintenance costs, data were
collected on parts inventories and equipment
breakdowns.
2.1.3 3
2.1.3.1 To reduce maintenance costs, data were collected on parts inventories
and equipment breakdowns.
2.1.4 4
2.1.4.1 To validate the model, inputs and outputs from the Lake Charles refinery were collected for
one month.
2.1.5 5
2.1.5.1 Running the LP yielded a daily strategy for running the refinery. For instance, the model might, say,
produce 400,000 gallons of turbine fuel using 300,000 gallons of crude 1 and 200,000 gallons of crude 2.
2.1.6 6-7
2.1.6.1 the model was used to guide day-to-day
refinery operations
2.2 The Supply Distribution Marketing
(SDM) System
2.2.1 1
2.2.1.1 CITGO wanted a mathematical model that could be used to make supply,
distribution, and marketing decisions such as:
2.2.1.1.1 1.Where should crude oil be purchased?
2.2.1.1.2 2. Where should products be sold?
2.2.1.1.3 3. price should be charged for products?
2.2.1.1.4 4. How much of each product should be held in inventory?
2.2.2 2
2.2.2.1 A database that kept track of sales, inventory, trades, and exchanges of all
refined products is installed.
2.2.3 3-5
2.2.3.1 The model makes all decisions mentioned in step 1.
2.2.4 4
2.2.4.1 The forecasting modules are continuously evaluated to ensure that they continue to give accurate
forecasts.
2.2.5 6-7
2.2.5.1 s. A new vice-president was appointed to coordinate the operation of the SDM and LP
refinery model. The product supply and product scheduling departments were combined
to improve communication and information flow.