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MODELS OF OPERATIONS RESEARCH

MODELS OF OPERATIONS RESEARCH – Notes for B.com/ BBA students

Posted on February 27, 2020February 20, 2025 By commerceiets

Table of Contents

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  • MODELS OF OPERATIONS RESEARCH
  • VARIOUS MODELS OF OPERATIONS RESEARCH
    • DIFFERENCE BETWEEN ANALYTICAL AND SIMULATION MODELS OF OPERATIONS RESEARCH
    • DIFFERENCE BETWEEN SYMBOLIC AND ANALOG MODEL

MODELS OF OPERATIONS RESEARCH

MODELS OF OPERATIONS RESEARCH
MODELS OF OPERATIONS RESEARCH

Most operations research studies involve the construction of a mathematical model. The models of Operations research is a collection of logical and mathematical relationships that represents aspects of the situation under study. Models describe important relationships between variables; include an objective function with which alternative solutions are evaluated, and constraints that restrict solutions to feasible values.

A model is always an abstraction that is of necessarily simpler than the real situation. Elements that are irrelevant or unimportant to the problem are to be ignored; hopefully leaving sufficient detail so that the solution obtained with the model has value with regard to the original problem.

Models must be both tractable, capable of being solved, and valid, representative of the original situation. These dual goals are often contradictory and are not always attainable. It is generally true that the most powerful solution methods can be applied to the simplest, or most abstract, model.

VARIOUS MODELS OF OPERATIONS RESEARCH

The following are the various models of Operations Research:

1.ANALYTICAL MODELS

An analytical model is quantitative in nature, and used to answer a specific question or make a specific design decision. Different analytical models are used to address different aspects of the system, such as its performance, reliability, or mass properties.

Analytical models must be expressed with sufficient precision that they can be formally analyzed, which is typically by a computer.

Analytical models can be further classified as:

  • Static Analytical Model
  • Dynamic Analytical Model

A static model represents the properties of a system that are independent of time, or true for any point in time. The properties being analyzed may have deterministic values, or may include probability distributions on their values.

A dynamic model is an analytical model that represents the time-varying state of the system, such as its acceleration, velocity, and position as a function of time.

The selection of a dynamic model versus a static model depends on the type of question that is being answered.

2. SIMULATION MODELS

Simulation models aim to replicate the workings and logic of a real system by using statistical descriptions of the activities involved.

A simulation model has ‘entities’ (e.g. machines, materials, people, etc.) and ‘activities’ (e.g. processing, transporting, etc.). It also has a description of the logic governing each activity. For example, a processing activity can only start when a certain quantity of working material is available, a person to run the machine and an empty conveyor to take away the product. Once an activity has started, a time to completion is calculated, often using a sample from a statistical distribution.

The model is started and continues to run over time, obeying the logical rules that have been set up. Results are then extracted concerning delays, etc.

It is clear that simulation models can replicate a complex production system. They can be used to indicate the level of shared resources needed by the operation (e.g. forklift trucks or operators), the speed of lines, sizes of vessels or storage tanks, etc.

3. ANALOG MODELS

Analog models represent the physiological process using elements that are, to some degree, analogous to those in the actual process. Good analog models can represent the system at a lower level, and in greater detail, than systems models, but not all analog models offer such detail. Analog models provide better representation of secondary features such as energy use, which is usually similar between analog elements and the actual components they represent.

4. SYMBOLIC MODELS

Symbolic Models also known as Mathematical Models are those which employ a set of symbols (i.e. letters numbers etc.) and functions to represent the decision variables and their relationships to describe the behavior or the system the symbols used generally mathematical or logical in character. They are by far the most widely employed in an O.R. study because of the great deal of complexity associated with an organization. A symbolic or mathematical model consists of a set of equations which define and specify the relationship and interactions among various elements of decision problem under study. The solution of the problem is then obtained by applying well-developed mathematical techniques to the model. The features of symbolic models are as follows:

  • It contains a set of representations (or symbols) of something.
  • It processes and manipulates those representations based on a set of rules programmed into the model.
  • The rules operate on the representations according to their ‘shape’ or syntax, not according to what they represent (their semantics).

5. ICONIC MODELS

Iconic model is also known as Physical Model. Iconic model is a physical representation of some item either in an idealized form or on a different scale i.e. a representation is an iconic model to the extent that its properties are the same as possessed by what it represents. A photograph, cyclograph, a blueprint and a painting are iconic models of persons or objects. The toy aero plane is an iconic model of a real aero plane. Commonly an iconic model represents a static event.

MODELS OF OPERATIONS RESEARCH
MODELS OF OPERATIONS RESEARCH

DIFFERENCE BETWEEN ANALYTICAL AND SIMULATION MODELS OF OPERATIONS RESEARCH

BASIS OF DIFFERENCE ANALYTICAL MODELS SIMULATION MODELS
MEANING Analytical analysis gives support to the idea theoretically and in mathematical equation. Simulation analysis shows that the idea is practically implementable or not.
COMPLEXITY These models try to include only most important aspects, so comparatively less complex. These models are very complex and detailed.
FLEXIBILITY These models are easier to change but small changes may bring big consequences. These models are hard to change if built once.
DATA These models need less to data to formulate. These models need more data to formulate.
COMPUTATIONAL COST These models incur less cost. These models incur heavy cost.

DIFFERENCE BETWEEN SYMBOLIC AND ANALOG MODEL

BASIS OF DIFFERENCE ANALOG MODEL SYMBOLIC MODEL
MEANING Analog model use one set of physical movements to represent another set of physical movements. It is a mathematical model that represents a problem with the use of symbols.
PRESENTATION They are presented in form of graphs, tables and curves. They are presented in form of mathematical equation.
NATURE The model is tangible. The model is intangible.
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Models of Operations Research
Models of Operations Research
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