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Introduction:OR APPROACH TO PROBLEM SOLVING, Observation

Introduction:Model Solution, Implementation of Results >>
Operations Research (MTH601)
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Mth 601
Operations Research
Handouts
Segment I: Introduction
Lectures 1-3
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Background
Technology - the application of science to the everyday Physical World - has, on the
whole, changed our lives greatly for the better, particularly since the time of Industrial
Revolution. Manufacturing industry, which supplies us with and at the same time creates the
wealth, which enables other services to exist, owes its existence to Science and Technology.
Some manufactured items, aircraft for example, are both complex and expensive, and
there are great difficulties, first of all in organizing their manufacture and then, once made, in
using them efficiently. Problems of this latter kind, often called systems problems, were studied
rigorously for the first time by scientists, not in industry but in the management of operations in
the 1939 - 45 war.
A number of teams of eminent scientists were employed by the British Government to
apply their expertise to management and operational problems rather than technical problems.
One such team (the Radar Operational Research team - which gave OR its name) was
responsible for implementing the installation and operation of radar after the technical
development work was complete.
Later on another team examined the relative ineffectiveness of the Allied Forces at
destroying the German U-boats, which were sinking the food convoy ships supplying Britain.
The OR team played an important part in reducing shipping losses and in the ultimate defeat of
the U-boats. With no precedent in the application of Science to the management function, the
scientists were still able to use their scientific approach-collecting information and developing
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hypothesis in order to come up with practical plans for the improvement of these wartime
operations.
After the end of the war, the same approach was used with great success in the industrial
and commercial field, developing most rapidly in Britain and the USA, followed by Europe and
the rest of the world. This has provided the basis for the evolution of Operational Research (OR)
as a separate and independent subject of Science. It is not based on any single academic
engineering, social science, economics, statistics and computing but is none of these. Then what
is OR?
DEFINING OPERATIONS RESEARCH:
OR has been defined in various ways and it is perhaps too early to define it in some
authoritative way. However given below are a few opinions about the definition of OR which
have been changed along-with the development of the subject.
In 1946 Morse & Kimbel has defined as;
"OR is a scientific method of providing executive departments with a quantitative
basis for decision regarding the operations under their control"
In 1948 Blackett defined as;
"OR is a scientific method of providing executives with any analytical and
objective basis for decisions"
Another definition is due to Morse who defined in 1948 as;
"The term OR, has here-to fore been used to connote various attempts to study
operations of war by scientific methods. From a more general point of view, OR
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can be considered to be an attempt to study those operations of modern society
which involved organizations of men or men and machines".
Later on in 1957, Churchmen Ackoff and Arnoff defined;
"OR is the application of scientific methods, techniques and tools to problems
involving the operations of systems so as to provide those in control of the
operations with optimum solutions to the problem".
In 1958 Saaty defined OR as;
"The art of giving bad answer to problems to which, otherwise, worse answers are
given".
The Operational Research Society of U.K. defines OR as:
"Operational Research is the application of the methods of science to complex
problems arising in the direction and management of large systems of men,
machines, materials and money in industry, business, government and defense.
The distinctive approach is to develop a scientific model of the system,
incorporating measurements of factors, such as chance and risk, with which to
compare the outcome of alternative decisions, strategies and controls. The
purpose is to help management determine its policies and actions scientifically."
In the USA, where it is called Operations Research, the OR Society of America says
more briefly;
"OR is concerned with scientifically deciding how to best design and operate
man-machine systems, usually under conditions requiring the allocation of scarce
resources".
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An even briefer definition might be "Science applied to management", but however, it
might be defined, there is no doubt that OR provides the numerate scientist - of whatever
discipline-with an opportunity to apply the skills of science in the field of Management.
Before proceeding further let us define for the sake of clarity some fundamental terms.
MANAGEMENT, MANAGEMENT SCIENCE AND OR:
MANAGEMENT may be equated with decision-making and control. Government
ministers manage the economy industrialists make decision within their companies and
individual make personal decisions.
MANAGEMENT SCIENCE is the study of problems as abstractions and the application
of the resulting theory to practical situations. Its two fundamental disciplines are behavioral
science and science and quantitative methods.
OPERATIONS RESEARCH (OR) is the application of quantitative methods to decision
making. It formulates problems incisively and assesses the possible consequence of alternative
course of action, so that informed and effective decisions can be taken.
OR APPROACH TO PROBLEM SOLVING:
OR encompasses a logical systematic approach to problem solving. This approach to
problem solving as shown in fig. 1 follows a generally recognized ordered set or steps: (1)
observation, (2) definition of the problems, (3) model construction, (4) model solution, and (5)
implementation of solution results.
OR PROCESS
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Observation
The first step in a problem solving exercises in OR is the identification of a problem that
exist in the system. This requires that the system be continuously and closely observed so that
problems can be identified as soon as they occur.
Definition of the Problem
Once it has determined that a problem exists, it must be clearly and concisely defined.
The problem definition includes the limits of the problems and the degree to which it pervades
other organs of the system. A requirement of problem definition is that the goals (or objective)
must be clearly defined which helps to focus attention on what the problem is.
Model Construction
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Table of Contents:
  1. Introduction:OR APPROACH TO PROBLEM SOLVING, Observation
  2. Introduction:Model Solution, Implementation of Results
  3. Introduction:USES OF OPERATIONS RESEARCH, Marketing, Personnel
  4. PERT / CPM:CONCEPT OF NETWORK, RULES FOR CONSTRUCTION OF NETWORK
  5. PERT / CPM:DUMMY ACTIVITIES, TO FIND THE CRITICAL PATH
  6. PERT / CPM:ALGORITHM FOR CRITICAL PATH, Free Slack
  7. PERT / CPM:Expected length of a critical path, Expected time and Critical path
  8. PERT / CPM:Expected time and Critical path
  9. PERT / CPM:RESOURCE SCHEDULING IN NETWORK
  10. PERT / CPM:Exercises
  11. Inventory Control:INVENTORY COSTS, INVENTORY MODELS (E.O.Q. MODELS)
  12. Inventory Control:Purchasing model with shortages
  13. Inventory Control:Manufacturing model with no shortages
  14. Inventory Control:Manufacturing model with shortages
  15. Inventory Control:ORDER QUANTITY WITH PRICE-BREAK
  16. Inventory Control:SOME DEFINITIONS, Computation of Safety Stock
  17. Linear Programming:Formulation of the Linear Programming Problem
  18. Linear Programming:Formulation of the Linear Programming Problem, Decision Variables
  19. Linear Programming:Model Constraints, Ingredients Mixing
  20. Linear Programming:VITAMIN CONTRIBUTION, Decision Variables
  21. Linear Programming:LINEAR PROGRAMMING PROBLEM
  22. Linear Programming:LIMITATIONS OF LINEAR PROGRAMMING
  23. Linear Programming:SOLUTION TO LINEAR PROGRAMMING PROBLEMS
  24. Linear Programming:SIMPLEX METHOD, Simplex Procedure
  25. Linear Programming:PRESENTATION IN TABULAR FORM - (SIMPLEX TABLE)
  26. Linear Programming:ARTIFICIAL VARIABLE TECHNIQUE
  27. Linear Programming:The Two Phase Method, First Iteration
  28. Linear Programming:VARIANTS OF THE SIMPLEX METHOD
  29. Linear Programming:Tie for the Leaving Basic Variable (Degeneracy)
  30. Linear Programming:Multiple or Alternative optimal Solutions
  31. Transportation Problems:TRANSPORTATION MODEL, Distribution centers
  32. Transportation Problems:FINDING AN INITIAL BASIC FEASIBLE SOLUTION
  33. Transportation Problems:MOVING TOWARDS OPTIMALITY
  34. Transportation Problems:DEGENERACY, Destination
  35. Transportation Problems:REVIEW QUESTIONS
  36. Assignment Problems:MATHEMATICAL FORMULATION OF THE PROBLEM
  37. Assignment Problems:SOLUTION OF AN ASSIGNMENT PROBLEM
  38. Queuing Theory:DEFINITION OF TERMS IN QUEUEING MODEL
  39. Queuing Theory:SINGLE-CHANNEL INFINITE-POPULATION MODEL
  40. Replacement Models:REPLACEMENT OF ITEMS WITH GRADUAL DETERIORATION
  41. Replacement Models:ITEMS DETERIORATING WITH TIME VALUE OF MONEY
  42. Dynamic Programming:FEATURES CHARECTERIZING DYNAMIC PROGRAMMING PROBLEMS
  43. Dynamic Programming:Analysis of the Result, One Stage Problem
  44. Miscellaneous:SEQUENCING, PROCESSING n JOBS THROUGH TWO MACHINES
  45. Miscellaneous:METHODS OF INTEGER PROGRAMMING SOLUTION