Quantitative Methods II (12 MBA22) Module I Introduction to Operation Research

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1 Learning Out Come Quantitative Methods II (12 MBA22) Module I Introduction to Operation Research After undergoing this Module the student must be able to exhibit the knowledge about The origin, meaning and definitions of OR Characteristics and scope of OR Advantages and Limitations of OR Model concept in OR Different types of classifying the Models in Practice with example 1.1. Origin and Development World War II : British military leaders asked scientists and engineers to analyze several military problems Deployment of radar Management of convoy, bombing, antisubmarine, and mining operations. called Military OR later Operations Research Project Scoop (Scientific Computation of Optimum Programs) simplex method for linear programs Lots of excitement, mathematical developments, queuing theory, thematical programming More excitement, more development and grand plans 1970 Disappointment, and a settling down. More realistic expectations Widespread availability of personal computers. Increasingly easy access to data. Widespread acceptance of managers to use models Improved use of O.R. systems. Further inroads of O.R. technology e.g., optimization and simulation add-ins to spreadsheets, modeling languages, large scale optimization

2 2000 and onwards - LOTS of opportunities for OR as a field E-business data + RFID Tag + The human genome project and its outgrowth + Need for more automated decision making + Need for increased coordination for efficient use of resources (Supply chain management) 1.2 Definition of Operation Research An art of winning war without actually fighting it OR is concerned with scientifically deciding how to best design and operate manmachine systems usually requiring the allocation of scarce resources. -OR Society, America O R is a scientific method of providing executive department with a quantitative basis for decisions regarding the operations under their control 1.3. Scope of OR HRM - Morse & Kimball To appoint the suitable persons on minimum salary To determine the best age of retirement Production To find the number and size of the items to be produced Optimum product mix Select, locate and design product mix Finance To maximize per capita income with minimum resources Find out profit plan for the company Best replacement policies Marketing Assignment of sales men for the territory Travelling sales man problem

3 1.4. CHARACTERISTICS OF OR Decision making-define the problem, select alternatives, determine the model to be used, choose the optimal An inter disciplinary approach to find out the optimum solution-requires team approach, blend of people. Scientific approach to obtain an optimal solution-no scope for guess work. Attempts to locate the best or optimal solution to the problem Digital compute 1.5 Advantages of O R Interdisciplinary Structured approach Tool for Decision support system Critical Analytical modeling results in almost accurate results Scope for wide business and general application Scope for applying AI and computing Machines. 1.6 Limitations of O R Conventional Thinking- Implementation of decision is delicate task Time consuming Costly- Money and Time cost Business variables under analysis are not static hence results are not consistent 1.7 concept of Model in Operation Research The approximation or abstraction maintaining only the essential elements of the system,which may be constructed in various forms by establishing relationship among specified variables and parameters of the system is called a model 1.8 Classification of Models A. Classification based on structure 1.Physical model-physical appearance of the real object either reduced in size or scaled up

4 a) Iconic model-used to describe the characteristics rather than explanatory Eg: Blue print of a house b) Analogue model-represent a system by the set of properties different from that of the original system and does not resemble physically Eg- organizational chart c)symbolic model-use letters, numbers or symbols o represent the relationship i) Verbal models-describe the situation in written or spoken language Eg: book ii) Mathematical models-use mathematical symbols, letters, nos., mathematical operation among variables, solution obtained by mathematic techniques B. Based on purpose 1. Descriptive models-describe the aspects of a situation based on observation, survey, questionnaire results Ex-block diagram 2. Predictive model-relate dependent and independent variables, and trying out what-if conditions 3. Normative models (optimization)-provides the best solution to certain limitations on the use of resources C. Based on time reference 1. Static model-represent system at time,no scope for including the changes Ex-inventory model depends on demand planning 2. Dynamic model-time is considered as one of the variable D. Based on degree of uncertainty 1. Deterministic model-constants and functional relationships are assumed to be known with certainty linear programming

5 2. Probabilistic models-one parameter or decision variable is a random variable percentage of pass E. Based on method of solution 1. Analytical models- have mathematical structure and solved by analytical techniques or mathematical.-optimization model 2. Simulation models- 1.9 Ideal model Simple to frame and easy to operate Least possible time for construction Based on less number of variables Flexible Expressing the relations and interrelations Advantages of models Provides economy in representation of the realities of a system Helps the decision maker to visualize the system Problem can be viewed by considering all its components Serve as a aid to transmit ideas Allows to analyze and experiment in complex situations Simplifies the investigation Summary of Learning At the end of the Module we have understood The origin, meaning and definitions of OR Characteristics and scope of OR Advantages and Limitations of OR Model concept in OR Different types of classifying the Models in Practice with example