1. MSE 606A Engineering Operations Research
Dr. Ahmad R. Sarfaraz Manufacturing Systems Engineering and Management
California State University, Northridge

2. Agenda Overview of Operations Research (OR)
Course syllabus and administration

3. Overview of Operations Research (OR)
What is Operations Research?
History of OR
Terminology
Who is leading?
Journals
Problem Domains of OR
Topics Covered
Nature of the OR Models
Some OR Applications
Phases of OR

4. What is Operations Research?
Systematic representation of real world systems by mathematical model(s) to help managers and engineers make better decisions
Can be used in a variety of organizations to solve many different types of problems
Problem Domains of OR
Business, Natural resources, Public administration, Military, Engineering, Telecommunications, Transportation, Nutrition, Public health, Network design

5. History of OR Initiated in UK during WWII
Used mathematical models to make decisions regarding the best utilization of war material
The term “Operational Research” [Research into (military) operations”
Established in the UK and USA by end of WWII
Diffused to industry, business, Gov’t.
Now, OR is a dominant decision-making tool

6. Terminology The British/European refers to “operational Research”
The Americans refer to “Operations Research”, or “Management Science”, and sometimes combine the terms together as “OR/MS”

7. Who is leading?
USA leads the world both in the practical application of OR and in advancing the theory
The American OR Conference have participants while the UK OR Conference has 300

8. Journals Operations Research Management Science
European Journal of Operational Research
Journal of Operational Research Society
Mathematical Programming
Networks
Naval Research Logistics
Interfaces
The first seven are theoretical while the last one focuses on applications

9. OR Models Deterministic Models
A given set of inputs or conditions repeatedly produce a fixed and completely predictable output.
Stochastic Models
More realistic situation wherein a given set of inputs or conditions produce random (or "probabilistic”) stochastic" outcomes.

10. OR Topics Deterministic Stochastic Linear “programming”
Transportation models
Assignment models
Network models
Project Management with CPM/PERT
Integer programming
Nonlinear programming
Goal Programming
Dynamic programming
Inventory Control
Stochastic
Game theory
Queuing theory
Markov chains
Decision analysis
Simulation
Inventory Control
Forecasting

11. Topics Covered Deterministic Linear Programming Model
Transportation and Assignment models
Network models
Project Management with CPM/PERT
Integer programming
Goal Programming
Inventory Control

12. Nature of the OR Models
Maximize area of a rectangular made of a wire of length L
Width and height of the rectangular?
Alternatives:
w and h as continuous variables (infinite)
Restriction:
2(w+h)=L
W,h>0
Objective Criterion:
Maximize Area=w*h

13. Nature of the OR Models
Maximize profit (sales revenue) given production capacity, demand restrictions , and other resources
Minimize total cost given minimum requirements

14. Format of the OR Models Maximize or Minimize Objective Function
Subject to:
Constraints

15. OR Application-Monsanto Corp.
Nature of Application
Optimize production operations in chemical plants to meet production targets
Related Topics
Integer Programming
Annual Savings
$2,000,000

16. OR Application-United Airlines
Nature of Application
Schedule shift work at reservation offices and airports to meet customer needs with minimum cost
Related Topics
LP, IP, Queuing Theory, and Forecasting
Annual Savings
$6,000,000

17. OR Application San Francisco Police Dept.
Nature of Application
schedule and deploy police patrol officers
with a computerized system
Related Topics
LP, IP, and Forecasting
Annual Savings
$11,000,000

18. OR Application-Texaco, Inc.
Nature of Application
Optimize the mix of ingredients into gasoline to meet quality and sales requirements
Related Topics
LP and NLP
Annual Savings
$30,000,000

19. OR Application-Citgo Petroleum Corp.
Nature of Application
Optimize refinery operations and the supply, distribution, and marketing of products
Related Topics
LP, Network, and Forecasting
Annual Savings
$70,000,000

20. OR Application-Delta Airlines
Nature of Application
Maximize the profit from assigning airplane types to over 2500 domestic flights
Related Topics IP
Annual Savings
$100,000,000

21. OR Application-Digital Equipment Corp.
Nature of Application
Restructure of global supply chain of suppliers, plants, distribution centers, potential sites, and market areas
Related Topics IP
Annual savings
$800,000,000

22. OR Application New Haven Health Department
Nature of Application
Design an effective needle exchange program to combat the spread of HIV/AIDS
Related Topics
OR Modeling
Annual Savings
33% less HIV/AIDS

23. Phases of OR Study Definition of the Problem Construction of the Model
Solution of the Model
Validation of the Model
Implementation of the Final Results

24. Definition of the Problem
Decision variables
What we want to decide?
Objective function
How we will decide?
Constraints
What binds our decision?
Parameters
What data and facts do we have?

25. Construction of the Model
What is a Model?
No general technique due to the type and complexity of the mathematical models
Select the most suitable model
Common OR models
LP, IP, DP, network programming, NLP
Simulation and Queuing models
Measures performance of the real systems

26. Validation of the Model
A model is valid if it can give a reasonable prediction of the system’s performance
Compare system’s performance with some past data for actual system

27. Implementation of the Final Results
Depends upon the support of top management, operating management, and the OR team

28. Phases of OR Modeling Observation Problem Definition Feedback Model
Techniques
Model
Construction
Model
Solution
Validation and
Implementation

29. Objectives Solid foundation in OR/MS
Math used as tool to solve problems
Applications oriented
Apply OR tools in your job
Foundation for further study

30. Organization First Session Second Secession
Introduction and motivation of new material, mathematical development
Second Secession
Solutions procedures, sample problems, and applications

31. Next Session LP Modeling Graphical Solution of LP problems
Objective functions
Decision variables
Constraints
Graphical Solution of LP problems