![8
1890
Frederick Taylor
Scientific
Management
[Industrial
Engineering]
1900
•Henry Gannt
[Project Scheduling]
•Andrey A. Markov
[Markov Processes]
•Assignment
[Networks]
1910
F. W. Harris
[Inventory Theory]
E. K. Erlang
[Queuing Theory]
1920
•William Shewart
[Control Charts]
•H.Dodge – H.Roming
[Quality Theory]
1930
Jon Von Neuman –
Oscar Morgenstern
[Game Theory]
1940
•World War 2
•George Dantzig
[Linear
Programming]
•First Computer
1950
•H.Kuhn - A.Tucker
[Non-Linear Prog.]
•Ralph Gomory
[Integer Prog.]
•PERT/CPM
•Richard Bellman
[Dynamic Prog.]
ORSA and TIMS
1960
•John D.C. Litle
[Queuing Theory]
•Simscript - GPSS
[Simulation]
1970
•Microcomputer
1980
•H. Karmarkar
[Linear Prog.]
•Personal computer
•OR/MS Softwares
1990
•Spreadsheet
Packages
•INFORMS
2019
•You are here](https://image.slidesharecdn.com/introductiontoor-221008063057-b72bd0ac/85/Introduction-to-OR-ppt-8-320.jpg)
Introduction to OR.ppt
- 1. 1 OPERATIONS RESEARCH Chapter 1 Introduction to Operations Research
- 2. What is Operations Research? 2 Operations The activities carried out in an organization. Research The process of observation and testing characterized by the scientific method. Operations Research is a quantitative approach to decision making based on the scientific method of problem solving.
- 3. • Operations Research is an Art and Science • An operation research (OR) is an analytical method of problem-solving and decision-making that is useful in the management of organizations. • In operations research, problems are broken down into basic components and then solved in defined steps by mathematical analysis. • 3
- 4. • Operations Research consists of: – The art of mathematical modeling of complex situations – The science of the development of solution techniques used to solve these models – The ability to effectively communicate the results to the decision maker 4
- 5. Model Development • Models are representations of real objects or situations. • Advantages of Models: – requires less time – is less expensive – involves less risk 5
- 6. 6 Operations Research Models • Linear Programming • Simulation • Network Optimization • Continuous-Time Markov Chains • Integer Programming • Queuing Theory (waiting lines) • Nonlinear Programming • Decision Analysis • Inventory Models • Game Theory
- 7. History of OR • OR is a relatively new discipline. • 70 years ago it would have been possible to study mathematics, physics or engineering at university it would not have been possible to study OR. • It was really only in the late 1930's that operationas research began in a systematic way. 7
- 8. 8 1890 Frederick Taylor Scientific Management [Industrial Engineering] 1900 •Henry Gannt [Project Scheduling] •Andrey A. Markov [Markov Processes] •Assignment [Networks] 1910 F. W. Harris [Inventory Theory] E. K. Erlang [Queuing Theory] 1920 •William Shewart [Control Charts] •H.Dodge – H.Roming [Quality Theory] 1930 Jon Von Neuman – Oscar Morgenstern [Game Theory] 1940 •World War 2 •George Dantzig [Linear Programming] •First Computer 1950 •H.Kuhn - A.Tucker [Non-Linear Prog.] •Ralph Gomory [Integer Prog.] •PERT/CPM •Richard Bellman [Dynamic Prog.] ORSA and TIMS 1960 •John D.C. Litle [Queuing Theory] •Simscript - GPSS [Simulation] 1970 •Microcomputer 1980 •H. Karmarkar [Linear Prog.] •Personal computer •OR/MS Softwares 1990 •Spreadsheet Packages •INFORMS 2019 •You are here
- 9. Problem Solving and Decision Making • 7 Steps of Problem Solving (First 5 steps are the process of decision making) – Identify and define the problem. – Determine the set of alternative solutions. – Determine the criteria for evaluating the alternatives. – Evaluate the alternatives. – Choose an alternative. – Implement the chosen alternative. – Evaluate the results. 9
- 10. Quantitative Analysis and Decision Making • Potential Reasons for a Quantitative Analysis Approach to Decision Making – The problem is complex. – The problem is very important. – The problem is new. – The problem is repetitive. 10
- 11. OR Application Areas • Strategic planning • Supply chain management • Pricing and revenue management • Logistics and site location • Optimization • Marketing research • Scheduling • Portfolio management • Inventory analysis • Forecasting • Sales analysis • Auctioning • Risk analysis
- 12. What you should know about Operations Research • How decision-making problems are characterized • OR terminology • What a model is and how to assess its value • How to go from a conceptual problem to a quantitative solution 12