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OR TECHINQUES or TOOLS
PRESENTED BY LIJIN MATHEW
B1 MBA
Techniques
1. Linear Programming
2. Queuing Theory3. Inventory Control
Method4. Net Work Analysis5. Replacement
Problems6. Sequencing7. Integer
Programming8. Assignment
Problems
9. Assignment Problems
10. Transportation Problems
11. Decision Theory and Game Theory
12. Markov Analysis13. Simulation14. Dynamic
Programming15. Goal Programming16. Symbolic Logic
Linear Programming
Linear programming technique is used to find solution for optimizing a given objective
objectives may be maximizing profit, minimizing cost, etc
This technique is used to allocate scare resources in an optimum manner in problems of scheduling ,product mix, etc
Queuing Theory
It is also called waiting line theory This theory deals with the situations in which queue
is formed eg: customers waiting for service, machines
waiting for repairmen, aircraft waiting for landing, etc It aims at minimizing the overall cost due to
servicing and waiting This technique is used to add new facilities to reduce
the cost of waiting time
Inventory Control Method
It aims at optimizing inventory levels Inventory planning answers two question how much to buy and when to buy
Net work Analysis
Net work are very popular and widely used quantitative technique
This model helps the managers to plan, schedule, monitor and control large projects, such as construction of building, making a ship, etc
It helps the managers to determine total project completion time, probability that a project will be completed by a certain date, least cost way of shortening total project completion time, etc
Program Evaluation Review Technique(PERT), Critical Path Method(CPM), Gantt chart are coming under net work analysis
Replacement Problems
It concerned with the situations arise when some items such as men, machine, electric bulbs, etc require replacement due to their decreasing efficiency, failure or down
It solves the replacement problems such as decisions regarding replacement in cost, return, etc.
Sequencing
This model developed to find a sequence for processing a job, so the total elapsed time for all the jobs will be minimum
It also helps to resolve the conflict between the objectives of maximizing machine utilization and complying with predetermined delivery dates
Integer Programming
Integer means complete or whole number One Important limitation of linear programming
model is the assumption that all the variables can take any value, may be decimal or fraction
When figures are rounded off the solution will be poor
By using integer programming algorithm a series of continuous linear programming problem solved in such a way that the solution containing unacceptable non-integer value are ruled out and the best higher programming solution is obtained
Assignment Problems
Special type of linear programming it deals with allocating the various resources
to various activities in such a way that the time or cost involved is to be minimized; sale or profit is maximized
Transportation Problems
It deals with transportation of a product from a number of sources with limited supplies to a number of destinations with specified demands at the minimum transportation cost
Aims to minimize the transportation cost
Decision Theories and Game Theories
Decision theory is primarily concerned with decision making under the conditions of risk and uncertainty
Game theory is concerned with decision making under conflict
The decision maker is to identify the best for situation In decision theory we can use decision tables and decision
trees, which can be used to graphically represent and solve decision making problem
The game theory assist the decision maker to have the knowledge of courses of action available to his opponent
Markov Analysis
Markov analysis permits one to predict changes over time when information about the behavior of a system is known
It is based on probability theories It allows a manager to determine future market
share both in the short run and long run If current situation is known, along with the
propensity of the system to change over time, it is possible to use Markov analysis to predict future conditions
Simulation
All real life problems cannot be stated in mathematical form
Simulation is a general technique that allows us to develop a dynamic model that acts like a real process
Developing a good simulation model is difficult but simulation allows us to solve problems that are difficult or impossible to solve otherwise
Dynamic Programming
It is introduced when the problems occur which have multi faced solutions
Here all possible results are analyzed and the best solution is selected
For solving each practical problem of specific dynamic programming, separate algorithm has to be developed
in dynamic programming computational work is reduced considerably
Goal Programming
In linear programming it focus on single objective and rest are taken as less important
In real practice there may be number of important objectives
Charles and Cooper developed “Goal programming in 1961”
In this several objective functions are considered, Each objective function has a fixed value called “target”
Goal Programming model is used to minimize deviations from these “targets”
Symbolic Logic
Symbols are more meaningful and accurate The whole problem is converted into algebraic
equations and propositions Business problems are not commonly converted into
symbols, but calculations are done on computers
15
Techniques
1. Linear Programming - solution for optimizing a given objective
2. Queuing Theory – to minimize the cost for queue3. Inventory Control Method – optimizing inventory levels, when
to buy and how much to buy4. Net Work Analysis - used to predict work completion time of
large project5. Replacement Problems – helps to take decisions regarding
replacement6. Sequencing – develop a sequence of process to do a job,
minimize time7. *Integer Programming – unacceptable non integer values are
ruled out8. Assignment Problems – allocating various resources to various
activities9. Transportation Problems – to minimize the transportation cost
of a product
Cont……
10. Decision Theory and Game Theory – decision making under risk and uncertainty, in conflict situations respectively
11. Markov Analysis – allows predict future market12. Simulation – developing dynamic model to solve real life
problems13. Dynamic Programming – multi faced solutions, selecting best
one14. *Goal Programming- several objectives “target” minimize
deviation from it15. Symbolic Logic – using symbols, problem is converted into
algebraic equations and propositions
Thank You…………………..