Ch 1.pptxOperations Research applies math tools to solve real-world decision problems. It helps in optimizing resources use in business, health, and engineering. Main steps are defining the problem, modeling, solving, and validating.
- 1. Program: Masters of Business Administration (MBA) Course Title: Management Science Course Code: MBA 5041 Credit Hours: 3 Course Instructor: Gojjam Ademe (PhD) Course Content: Courseoutline.docx 1 By Gojjam A.
- 2. 06/04/2025 2 Chapter One: Introduction to MS(OR)
- 3. 06/04/2025 3 Introduction • The subject Management Science (MS) or Operations Research (OR) is a branch of Mathematics- specially applied mathematics, used to provide a scientific base for management to take timely and effective decisions to their problems. • It tries to avoid the dangers from taking decisions merely by guessing or by using thumb rules. • It uses a logical approach to problem solving (uses quantitative models to solve business problems)
- 4. 06/04/2025 4 Introduction • Management is multidimensional and dynamic concept • It is multidimensional, because management problems and their solutions have consequences in several dimensions, such as human, economic, social and political fields. • It is dynamic, because the manager operates his/her system in an environment which will never remain static.
- 5. 06/04/2025 5 Introduction • The general OR approach is to analyze the problem in economic terms and then implement the solution if it doesn’t be aggressive or violent to other aspects like human, social, and political constraints. • Quantitative approach to management problems requires that decision problems be defined, analyzed, and solved in a conscious, rational, logical and systematic and scientific manner- based on data, facts, information, and logic, and not mere guess work or thumb rules.
- 6. 06/04/2025 6 Introduction • OR is the body of knowledge, which uses mathematical techniques to solve management problems and make timely and optimal solutions. • OR is a discipline that deals with the application of advanced analytical methods to help make better decisions • Though common sense, experience and commitment of the manager is essential in making decision, we can not deny the role-played by scientific methods in making optimal decisions. • The applications of Management Science /OR/ techniques are widespread, and they have been frequently credited with increasing the efficiency and productivity of business firms.
- 7. 06/04/2025 7 History of Operations Research • OR is a “war baby” • It is because the 1st problem attempted to solve in a systematic way was concerned with how to set the time fuse bomb to be dropped from an aircraft onto a submarine. • The main origin of OR was during the WWII. • The name operations research evolved in the year 1940 (WWII was from September 1, 1939–September 2, 1945) • During WWII, the military management in England invited a team of scientists to study the strategic and tactical problems related to air and land defense of the country.
- 8. 06/04/2025 8 History of Operations Research • The problem attained importance because at that time resources available with England was very limited and objective was to win the war with available meager resources. • It was necessary to decide upon the most effective utilization of available resources to achieve the objective. • As the name indicates: o OPERATION is used to refer to military problem o RESEARCH is used to refer to inventing new method
- 9. 06/04/2025 9 History of Operations Research • As this method of solving problem was invented during the war period, the subject is given the name “OPERATIONS RESEARCH” and is abbreviated as OR. • After the war ended, scientists who had been active in the military Operation groups made efforts to apply the operations research approach to civilian problems, related to business, industry, research and development, etc. • After the world war, there was a scarcity of industrial material and industrial productivity which calls for the use of OR • OR today plays a significant role in support of management decision making in business and non-business organizations
- 10. 06/04/2025 10 History of Operations Research • There are three important factors behind the rapid development in the use of operations research approach. 1. The economic and industrial boom after World War II resulted in continuous mechanization, automation, decentralization of operations and division of management factors. 2. Many operation researchers continued their research after the war ended. E.g established different OR techniques. 3. Analytic power was made available by high-speed computers.
- 11. 06/04/2025 11 Definitions of Operation Research OR can be defined in different ways by different groups. Following are some of the important definitions in academic interest. OR is the art of winning wars without actually fighting (Aurther Clarke) OR is the art of giving bad answers to problems where otherwise worse answers are given (T.L. Satty) OR is the application of scientific methods, techniques and tools, to problems involving operations of a system so as to provide those in control of the operations with optimum solutions to the problems.
- 12. 06/04/2025 12 Definitions of Operation Research OR is a scientific method for providing executive departments a quantitative basis for decisions regarding the operations under their control (Morse and Kimball) OR is the application of scientific methods, techniques and tools to operations of a system with optimum solutions to the problem (Churchman, Ackoff and Arnoff)
- 13. 06/04/2025 13 Definitions of Operation Research OR seeks the determination of the optimum course of action of a decision problem under the restriction of limited resources. It is quite often associated almost exclusively with the use of mathematical techniques to model and analyze decision problems. OR is the application of a scientific approach to solving management problems in order to help managers make better decisions
- 14. 06/04/2025 14 Nature and significance of OR • The OR approach is particularly useful in balancing conflicting objectives (goals or interests), where there are many alternative courses of action available to the decision-makers. • In a theoretical sense, the optimum decision must be one that is best for the organization as a whole. • It is often called global optimum. A decision that is best for one or more sections of the organization is usually called suboptimum decision.
- 15. 06/04/2025 15 Nature and significance of OR • Hence, the OR approach attempts to find global optimum by analyzing inter- relationships among the system components involved in the problem. • That means, in OR, we are concerned with how to choose optimal strategy under specified set of assumptions, including all available strategies and their associated payoffs.
- 16. 06/04/2025 16 Features of Operations Research Approach 1. OR is an Inter-disciplinary team approach: Interdisciplinary teamwork is essential because while attempting to solve a complex management problem, one person may not have complete knowledge of all its aspects such as economic, social, political, psychological, engineering, etc. 2. Methodological Approach: OR is the application of scientific methods, techniques and tools to problems involving the operations of systems so as to provide those in control of operations with optimum solutions to the problems.
- 17. 06/04/2025 17 Features of Operations Research Approach 3. Holistic Approach or Systems Orientation: While arriving at a decision, an operation research team examines the relative importance of all conflicting and multiple objectives and the validity of claims of various departments of the organization from the perspective of the whole organization. 4. Objectivistic Approach: The OR approach seeks to obtain an optimal solution to the problem under analysis.
- 18. 06/04/2025 18 Features of Operations Research Approach 5. Decision Making: OR increases the effectiveness of management decisions. It is the decision science which helps management to make better decisions. 6. Use of Computers: OR often requires a computer to solve the complex mathematical model or to perform a large number of computations that are involved. 7. Human factors
- 19. 06/04/2025 19 Model and Modeling in Operations Research • A Model is an abstraction of reality. It is a simplified, and often idealized, representation of reality. • Model provide a manager or analyst with an alternative to working directly with reality. • It is important to carefully decide which aspect of reality to include in a model.
- 20. 06/04/2025 20 Model Types • Models can be classified in a number of ways. One way uses these categories • Iconic models- are the least abstract; they are physical models that look like reality. Eg. Model of a car • Analog Models- are also physical models but they are more abstract than iconic models. E.g. Graph • Symbolic Models- are the most abstract: they incorporate numbers and algebraic symbols to represent important aspects of a problem, often in equation form. E.g. LP models
- 21. 06/04/2025 21 Model and Modeling in Operations Research • We can define OR Model as some sort of mathematical or theoretical description of various variables of a system representing some aspect of a problem on some subject of interest or inquiry. • The model enables to conduct a number of experiment involving theoretical subjective manipulations to find some optimum solution to the problem on hand
- 22. 06/04/2025 22 Modeling process Real world problems Observation and defining a problem Formulating the model Solving the Mathematical Model Validating (Testing) the solution Implementing the solution yes Modify the model No
- 23. 06/04/2025 23 Step 1: Observation and defining a problem • The first step in OR process is the identification of a problem that exists is a system (organization). • The system must be continuously and closely observed so that problems can be identified as soon as they occur or anticipated. • Problems are not always the results of crisis; but instead frequently involve an anticipatory or planning situation. • Once it has been determined that a problem exists, the problem must be clearly and concisely defined.
- 24. 06/04/2025 24 Step 2: Formulating a model • Model formulation involves an analysis of the system under study, determining objective of the decision- maker, and alternative course of action, etc, so as to understand and describe, in precise terms, the problem that an organization faces.
- 25. 06/04/2025 25 Step 3: Solving the Mathematical Model • This involves obtaining the numerical values of decision variables. • Obtaining these values depends on the specific form or type of mathematical models. • Solving the model requires the use of various mathematical tools and numerical procedures. • In general, there are two categories of methods used for solving an OR model. 1. Graphic method 2. Simplex method
- 26. 06/04/2025 26 Step 4: Validating (Testing) the solution • After solving the mathematical model, it is important to review the solution carefully to see that values make sense and that the resulting decisions can be implemented. • Some of the reasons for validating the solution are: (i) The mathematical model may not have enumerated all the limitations of the problem under consideration. (ii) Certain aspect of the problem may have been overlooked, omitted or simplified, (iii) The data may have been incorrectly estimated or recorded, perhaps when entered in to the computer.
- 27. 06/04/2025 27 Step 5: Implementing the solution • The decision-maker has not only to identify good decision alternatives but also to select alternatives that are capable of being implemented. • It is important to ensure that any solution implemented is continually reviewed and updated in light of a changing environment.
- 28. 06/04/2025 28 Operations Research Techniques 1. Linear Mathematical Programming - Linear programming models -Graphic Analysis -Simplex Method - Post optimality -Transportation and assignment - Integer linear programming -Goal Linear 2. Probabilistic Techniques -Probability - Decision Analysis -Game Theory -Markov Analysis -Queuing -Simulation -Forecasting
- 29. 06/04/2025 29 Operations Research Techniques 3. Inventory Techniques -Certain Demand -Uncertain Demand 4. Net work Techniques -Net work flow CPM/PERT 5. Other linear and nonlinear Techniques • Dynamic Programming • Break-even Analysis • Non-linear programming
- 30. Thank you Questions and Comments