5. INTRODUCTION TO LINEAR PROGRAMMING (LP) Learning Objectives 1. Obtain an overview of the kinds of problems linear programming has been used to solve. 2. Learn how to develop linear programming models for simple problems. 3. Be able to identify the special features of a model that make it a linear programming model. 4. Learn how to solve two variable linear programming models by the graphical solution procedure. 5. Understand the importance of extreme points in
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1ST GENERATION (MACHINE CODE): The first generation of codes used to program a computer‚ was called machine language or machine code‚ it is the only language a computer really understands‚ a sequence of 0s and 1s that the computer’s controls interprets as instructions‚ electrically. First-generation languages required the writing of long strings of binary numbers to represent such operations as “add‚” “subtract‚” “and compare.” Later improvements allowed octal‚ decimal‚ or hexadecimal representation
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computers in this field. [5 Marks] 2. Explain how the linear programming technique can be helpful in decision-making in the areas of Marketing and Finance. [10 Marks] 3. a. How do you recognise optimality in the simplex method? b. Write the role of pivot element in simplex table? [5 Marks] [5 Marks] 4. What is the significance of duality theory of linear programming? Describe the general rules for writing the dual of a linear programming problem. [10 Marks] 5. Use Two-Phase simplex method
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limitations. Quantitative approach to decision making‚ models & modeling in Operations Research. Module II (8 Hours) Linear programming‚ Structure of linear program model‚ Assumption‚ Advantages‚ Limitations‚ General mathematical model‚ Guidelines for formulation of linear programming model‚ Graphical method‚ algorithm (Only illustrative problems) Duality in linear programming.. Module III (8 Hours) Transportation problem‚ General structure of transportation problem‚ methods of finding initial
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within 2 hours of opening it - Content: - General knowledge on the background of operations research/management science - Value of operations research/management science - Modeling basics (types‚ applications‚ etc.) - Linear programming/Integer Linear Programming basics (difference between the two‚ building an LP/ILP model‚ integration of the model into Excel‚ optimal solution‚ feasible region‚ establishing constraints‚ bounded/unbounded solutions‚ sensitivity analysis) - Network Modeling
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order to provide Mr. Rodriguez with the information he requested‚ linear programming will be utilized. Linear programming is the “several related mathematical techniques used to allocate limited resources among competing demands in an optimal way” (Jacobs & Chase‚ 2013‚ appendix
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Linear Regression & Best Line Analysis Linear regression is used to make predictions about a single value. Linear regression involves discovering the equation for a line that most nearly fits the given data. That linear equation is then used to predict values for the data. A popular method of using the Linear Regression is to construct Linear Regression Channel lines. Developed by Gilbert Raff‚ the channel is constructed by plotting two parallel‚ middle lines above and below a Linear Regression
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whereas each bracelet requires 2 ounces of gold and 5 ounces of platinum. The store has to use a minimum of two ounces of gold. The demand for bracelet is no less than three. A necklace earns $375 in profit and a bracelet‚ $225. Formulate a linear programming model for this problem with an appropriate objective function =number of necklaces to be made = number of bracelets to be made Maximize Profit (Z)= Subject to Maximum availability of gold Minimum usage quantity of gold Maximum availability
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Simulation with ARENA Khalil Management of Technology Kolarik Creating Quality: Concepts‚ Systems‚ Strategies‚ and Tools Creating Quality: Process Design for Results Law and Kelton Simulation Modeling and Analysis Nash and Sofer Linear and Nonlinear Programming Nelson Stochastic Modeling: Analysis and Simulation Niebel and Freivalds Methods‚
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performance of the system. Techniques and tools of operation research: Linear programming: You can use linear programming to find a solution for optimising a given objective. The objective may be to maximize profit or to minimize cost. Inventory control methods: The production‚ purchasing‚ and material managers are always confronted with questions‚ such as when To buy‚ and how much to keep in stock. Goal programming: In linear programming ‚ you take a single objective function and consider all other factors
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