RESOLUTION AND MODELING PROBLEMS WITH PL

Andres  Arteaga
Mind Map by Andres Arteaga, updated more than 1 year ago
Andres  Arteaga
Created by Andres Arteaga almost 4 years ago
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Mapa mental seven step model

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RESOLUTION AND MODELING PROBLEMS WITH PL
1 The seven step model building process
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.
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