State the different types of models used in OR?

State the different types of models used in OR. Explain briefly the general methods for solving these OR models?

rahul kant

Operations research (OR) is a discipline explicitly devoted to aiding decision makers.
This section reviews the terminology of OR, a process for addressing practical decision problems and the relation between Excel models and OR.

The different types of model are as following:

Linear Programming

Network Flow Programming

Integer Programming

Nonlinear Programming

Dynamic Programming

Stochastic Programming

Combinatorial Optimization

Discrete Time Markov Chains

Continuous Time Markov Chains

Simulation

Give me the details of different types of models used in OR Gate I want to know about OR gate because I have no idea about it.

I am doing MBA final year student and searching for details about Types Of Models Used In OR. Will you provide Types Of Models Used In OR and also tell state the difference?

Operations research (OR) is a discipline explicitly devoted to aiding decision makers.

This section reviews the terminology of OR, a process for addressing practical decision problems and the relation between Excel models and OR.

A model is an idealized representation or abstraction of a real-life system.

The objective of a model is to identify significant factors that affect the real-life system and their interrelationships.

Types Of Models Used In OR

You can broadly classify OR models into the following types.

a. Physical Models include all form of diagrams, graphs and charts. They are designed to tackle specific problems. They bring out significant factors and interrelationships in pictorial form to facilitate analysis. There are two types of physical models:

I. Iconic models

II. Analog models

Iconic models are primarily images of objects or systems, represented on a smaller scale. These models can simulate the actual performance of a product. Analog models are small physical systems having characteristics similar to the objects they represent, such as toys.

b. Mathematical or Symbolic Models employ a set of mathematical symbols to represent the decision variable of the system. The variables are related by mathematical systems. Some examples of mathematical models are allocation, sequencing, and replacement models.

c. By nature of Environment: Models can be further classified as follows:

I. Deterministic model in which everything is defined and the results are certain, such as an EOQ model.

II. Probabilistic Models in which the input and output variables follow a defined probability distribution, such as the Games Theory.

d. By the extent of Generality Models can be further classified as follows:

I. General Models are the models which you can apply in general to any problem. For example: Linear programming.

II. Specific Models on the other hand are models that you can apply only under specific conditions. For example: You can use the sales response curve or equation as a function of only in the marketing function.

Solution

After deciding on an appropriate model you need to develop a solution for the model and interpret the solution in the context of the given problem. A solution to a model implies determination of a specific set of decision variables that would yield an optimum solution.

An optimum solution is one which maximizes or minimizes the performance of any measure in a model subject to the conditions and constraints imposed on the model.

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