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UNIT-I
INTRODUCTION
To Decision Science: History of Operations Research/Decision Science, Definition and Features of Decision Science. Approach to Problem Solving, Methodology of Decision Science, Opportunities and Shortcomings of the Decision Science Approach, Applications of Decision Science. Computer Software for Decision Science.
UNIT-II
Introduction to Linear Programming
Structure of Linear Programming Model, Advantages and Limitations of Linear Programming, Application
Areas of Linear Programming, General Mathematical Model of Linear Programming Problems, Guidelines of Linear Programming Model Formulation.
UNIT-III
Methods of Linear Programming-I
The Graphical Method, Important Definitions, Extreme Point Solution Method, Examples on Maximization LP Problem, Examples on Minimization LP Problem; Examples on Mixed Constraints LP Problem, Iso-Profit (Cost) Function Line Method.
UNIT-IV
Methods of Linear Programming-II
The Simplex Method, Simplex Algorithm (Maximization Case), Simplex Algorithm (Minimization Case), Two Phase Method, Big M Method, Some Complications and their Resolutions: Unrestricted Variables, Tie for Entering Basic Variable, Tie for Leaving Basic Variable, Degeneracy.
UNIT-V
Exploratory Data Analysis
Exploring Central Tendency of Data, Exploring Dispersion of Data in Terms of Standard Deviation, Skewness and Kurtosis, Standard Error of Mean, Designing Confidence Intervals, Identifying Outliers through Box Plot.
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CategoriesArts and Science
Format EPUB
TypeeBook