Introduction to Operation Research

Topics to be covered What is Operation Research Modeling in Operation Research Scope of Operation Research Limitations of Operation Research Difficulties of Operation Research

What is Operation Research Operations research is the application of scientific methods, techniques and tools to problems involving the operations of the system so as to provide those in control of the system with optimum solutions to the problems Back

Modeling in Operation Research A model is defined as a representation of an actual object or situation. Since a model is an abstraction of reality, it thus appears to be less complete than reality itself. The main objective of a model is to provide means for analyzing the behavior of the system for the purpose of improving its performance.

Models can be classified according to following characteristics: Classification by structure (i) Iconic Models: Iconic models represent the system as it is by scaling it up or down( by enlarging or reducing the size) Example: A toy airplane is an iconic model of a real one. Other examples are photographs, drawings, maps etc. (ii) Analogue Models: the models in which one set of properties is used to represent another set of properties. Are called analogue models. Example: In graphs, distance is used to represent properties like time,percent,age.

(iii) Mathematical models: The mathematical model is one which employs a set of mathematical symbols to represent the decision variables of the system. These variables are related together by means of mathematical equation or a set of equations to describe the behavior of the system. After that mathematical techniques is applied to get the solution. Classification by purpose (i) Descriptive models: A descriptive model simply describe some aspects of a situation based on observations, survey. The result of an opinion poll represents a descriptive model.

(ii) Predictive Models: Such models can answer ‘What if’ type of questions i.e. they can make predictions regarding certain events. Example: Television networks predict the election results before all the votes actually counted. (iii) Prescriptive Models: Finally, when a predictive model has been repeatedly successful, it can be used to prescribe a source of action. Example: linear programming prescribes what the managers ought to do.

Classification by nature of environment (i) Deterministic Models: Such models assume conditions of complete certainty and perfect knowledge. Example: Linear programming, Transportation and assignment models are deterministic models. (ii) Probabilistic models: These type of models usually handle such situations in which the consequences of managerial actions cannot be predicted with certainty. However it is possible to forecast a pattern of events, based on which managerial decisions can be made. Example: Insurance companies are willing to insure against risk of fire, accidents, sickness and so on.

Classification by behavior (i) Static Models: These models do not consider the impact of changes that take place during the planning. (ii) Dynamic Models: In these models, time is considered as one of the important variables and admit the impact of changes generated by time.

Classification by method of solution (i) Analytical Models: These models have a specific mathematical structure and thus can be solved by mathematical techniques. Example: Linear programming model, transportation and assignment models are analytical models. (ii) Simulation Models: They also have a mathematical structure but they cannot be solved by using tools and techniques of mathematics. Classification by use of digital computers Quantitive models: Such models are used to measure the observations. Example: degree of temperature etc. Back

Scope of operation research Operation research is very important in various fields. 1. In agriculture: With the explosion of population, every country is facing the problem of- (i) Optimum allocation of land to various crops. (ii) Optimum distribution of water from various resources for irrigation purposes. 2. In finance: Operation techniques can be applied here: (i) To maximize the per capital income with minimum resources. (ii)To find out the profit plan for the company (iii) To determine the best plan policies.

3. In Industry: If the industry manager decides his policies only on the basis of his past experience and a day comes when he gets retirement, then a heavy loss is encountered. This heavy loss can immediately be compensated by newly appointing a young specialist of or techniques in business management. 4. In marketing: With the help of or techniques, a marketing administrator can decide: (i) Where to distribute the products for sale sothat total cost of transportation is minimum. (ii) The size of stock to meet the future demand. (iii) How to select the best advertising media with respect to time, cost etc.

5. In personnel Management: A personal manager can use or techniques. (i) To appoint the most suitable persons on minimum salary. (ii) To determine the best age of retirement for the employees. (iii) To find out the number of persons to be appointed on full time basis. 6. In LIC: OR approach is also applicable to enable the LIC offices to decide: (i) What should be the premium rates for various modes of policies (ii) How best the profits could be distributed. Back

Limitations of OR 1) Mathematical models with are essence of OR do not take into account qualitative factors or emotional factors. 2) Mathematical models are applicable to only specific categories of problems 3) Being a new field, there is a resistance from the employees the new proposals. 4) Management may offer a lot of resistance due to conventional thinking. 5) OR is meant for men not that man is meant for it. Back

Difficulties of OR 1) The problem formulation phase 2) Data collection 3) Operations analyst is based on his observation in the past 4) Observations can never be more than a sample of the whole 5) Good solution to the problem at right time may be much more useful than perfect solutions. Back

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