TYPES OF OPERATION RESEARCH MODELS. A MODEL is a representation of the reality. Most of our thinking of operations research in business take place in.

Slides:

Advertisements

Similar presentations

1 1 Slide Chapter 1 & Lecture Slide Body of Knowledge n Management science Is an approach to decision making based on the scientific method Is.

Advertisements

Indira Gandhi National Open University presents. Course: System Constructs and Tools By NEERJA PAHWA SARDANA A Video Lecture.

INTRODUCTION TO MODELING

Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall.

Topic 2. DECISION-MAKING TOOLS

Chapter 1 DECISION MODELING OVERVIEW. MGS 3100 Business Analysis Why is this class worth taking? –Knowledge of business analysis and MS Excel are core.

Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall Publishers and Ardith E. Baker.

DECISION SUPPORT SYSTEM ARCHITECTURE: THE MODEL COMPONENT.

Research Methods in MIS

Marakas: Decision Support Systems, 2nd Edition © 2003, Prentice-Hall Chapter Chapter 4: Modeling Decision Processes Decision Support Systems in the.

Introduction to Modeling

Objectives Explain how scientists use statistics.

Brown, Suter, and Churchill Basic Marketing Research (8 th Edition) © 2014 CENGAGE Learning Basic Marketing Research Customer Insights and Managerial Action.

Marketing Research MR2300 Paul Tilley. What is Marketing Research? Marketing research is the systematic and objective process of gathering information.

Introduction to Quantitative Techniques

Stevenson and Ozgur First Edition Introduction to Management Science with Spreadsheets McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies,

Accounting Information Systems, 1st Edition

A2 Business Studies Unit 3. Aim: Understand the use of correlation and ICT in marketing. Objectives: Define correlation. Explain correlation relationships.

Quantitative Business Analysis Course Introduction By Aziza Munir.

System Modeling Nur Aini Masruroh.

Introduction to Operation Research

Lecture 4 Transport Network and Flows. Mobility, Space and Place Transport is the vector by which movement and mobility is facilitated. It represents.

Modeling & Simulation: An Introduction Some slides in this presentation have been copyrighted to Dr. Amr Elmougy.

Managing Organizations Informed decision making as a prerequisite for success Action Vision Mission Organizational Context Policies, Goals, and Objectives.

1 OM2, Supplementary Ch. D Simulation ©2010 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible.

Tools of Environmental ScienceSection 2 Section 2: Statistics and Models Preview Bellringer Objectives How Scientists use Statistics Statistics Works with.

Modeling and Analysis By Dr.S.Sridhar,Ph.D., RACI(Paris),RZFM(Germany),RMR(USA),RIEEEProc. web-site :

Introduction to Modeling Introduction Management Models Simulate business activities and decisions Feedback about and forecast of outcomes Minimal risk.

Introduction to Climate Prediction Objective You will begin to understand what happens to radiation from the Sun when it gets to the Earth and what this.

Chapter 4 MODELING AND ANALYSIS. Model component Data component provides input data User interface displays solution It is the model component of a DSS.

Introduction to Management Science

Scientific Paper. Elements Title, Abstract, Introduction, Methods and Materials, Results, Discussion, Literature Cited Title, Abstract, Introduction,

1 ISA&D7‏/8‏/ ISA&D7‏/8‏/2013 Methodologies of the SDLC Traditional Approach to SDLC Object-Oriented Approach to SDLC CASE Tools.

MGS3100_01.ppt/Aug 25, 2015/Page 1 Georgia State University - Confidential MGS 3100 Business Analysis Introduction - Why Business Analysis Aug 25 and 26,

Chapter McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Risk and Capital Budgeting 13.

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J F-1 Operations.

Chapter 1 Introduction n Introduction: Problem Solving and Decision Making n Quantitative Analysis and Decision Making n Quantitative Analysis n Model.

Topics Covered:  System System  Sub system Sub system  Characteristics of System Characteristics of System  Elements of Systems Elements of Systems.

Developing the theoretical and conceptual framework From R.E.Khan ( J199 lecture)

Risk Analysis in Capital Budgeting. Nature of Risk Risk exists because of the inability of the decision-maker to make perfect forecasts. the risk associated.

Objectives of the Session By the end of this session, it will be hoped to achieve the following objectives;  To understand the nature and scope of managerial.

OPERATING SYSTEMS CS 3530 Summer 2014 Systems and Models Chapter 03.

Models in Science.

Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 4: Modeling and Analysis.

Science and Engineering Practices K–2 Condensed Practices3–5 Condensed Practices6–8 Condensed Practices9–12 Condensed Practices Developing and Using Models.

Modeling in the NGSS NGSS: Students should have opportunities to – Use models – Develop models – Test, evaluate, and revise models.

OPERATION RESEARCH (EOE-073) 1. 2 Introduction Operations Research is an Art and Science It had its early roots in World War II and is flourishing in.

NETW 707: Modeling & Simulation Course Instructor: Tallal Elshabrawy Instructor Office: C3.321 Instructor Teaching.

F5 Performance Management. 2 Section C: Budgeting Designed to give you knowledge and application of: C1. Objectives C2. Budgetary systems C3. Types of.

© 2008 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.

Objectives Explain how scientists use statistics. Explain why the size of a statistical sample is important. Describe three types of models commonly used.

26134 Business Statistics Week 4 Tutorial Simple Linear Regression Key concepts in this tutorial are listed below 1. Detecting.

Design Communication. Freehand Drawing Definition: The spontaneous representation of ideas on paper without the use of technical aids.

Yandell - Econ 216 Chap 1-1 Chapter 1 Introduction and Data Collection.

Prepared by John Swearingen

Chapter 4 Modeling and Analysis

OPERATING SYSTEMS CS 3502 Fall 2017

Section 2: Statistics and Models

Section 2: Statistics and Models

DSS & Warehousing Systems

Introduction to Modeling

Research Methods in Psychology

Quantitative Techniques

Learning Objectives By the end of this lesson students should:

Functions Introduction.

Section 2: Statistics and Models

SIMULATION IN THE FINANCE INDUSTRY BY HARESH JANI

Introduction to Decision Sciences

Presentation transcript:

TYPES OF OPERATION RESEARCH MODELS

A MODEL is a representation of the reality. Most of our thinking of operations research in business take place in the context of models. The objective of model is not to identify all aspects of the situation but to identify significant factors and their intre- relationship. A major advantage of modelling is that it permits the decision maker to examine the behaviour of a system without interfering with as going operations.

TYPES OF OR MODELS TYPES OF OR MODELS PHYSICAL MODELS MATHEMATICAL MODELS BY NATURE OF ENVIRONMENT BY THE EXTENT OF GENERALITY ICONIC MODELS ANALOG MODELS DETERMINISTIC MODELS PROBABALISTIC MODES GENERAL MODELS SPECIFIC MOELS

(A) PHYSICAL MODELS These models include all forms of diagrams, drawings graphs and charts. Most of which are designed to deal with specific types of problems. By presenting significant factors and inter-relationships in pictorial term, physical models are able to a problem in a manner that facilitates analysis. There are two types of physical models which are explained as follows:  ICONIC MODELS An icon is an image or likeness of an object or system it represents. An iconic model the least abstract physical replica of a system, is usually based on a smaller scale than original. These models can stimulate the actual performance of a product thereby availing the treamenduous expense of designing full scale experimental models.

 ANALOG MODELS Analog models are closely associated with iconic models. However they are not replicas of problem situations. Rather, they are small physical systems that have similar characteristics and work like an object or systems it represents e.g children’s toys model of rails, roads etc., whereas the actual objects are complex and might not allow direct handling or manipulations. (B) MATHEMATICAL MODELS Symbolic models employ a set of mathematical symbols to represent the decision variable of the system under study. These variables are related together by mathematical equations. Following are the examples of mathematical models which have been applied to business and industry.

- ALLOCATION MODEL - ROUTING MODEL - QUEUING MODEL - SIMULATION - REPLACEMENT MODEL - MARKOV’S ANALYSIS - SEQUENCING MODEL (C) BY NATURE OF ENVIRONMENT  DETERMINISTIC MODELS In this model every thing is defined and the results are certain. Certainty is the state of nature assumed in these models.

 PROBABALISTIC MODEL In cases of risk and uncertainty, the input and output variables take the form of probability of occurrence of an event. (D) BY THE EXTENT OF GENERALITY  GENERAL MODELS General model is one in which does not apply one situation only rather it has got general applications.  SPECIFIC MODEL Specific model is applicable under specific condition only e.g. sales response curve, or equation as a function of advertising is applicable in marketing function alone.

THANK YOU