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QUANTITATIVE METHODS-I (Code: IMN105)

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QUANTITATIVE METHODS-I  SOLVED PAPERS AND GUESS 

 

Product Details:  QUANTITATIVE METHODS-I   SOLVED PAPERS AND GUESS

Format: BOOK  

Pub. Date: NEW EDITION APPLICABLE FOR Current EXAM

Publisher: MEHTA SOLUTIONS

Edition Description: 2016-17

 

        RATING OF BOOK: EXCELLENT

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  If you find yourself getting fed up and frustrated with other ignou book solutions now mehta solutions brings top solutions for Biju Patnaik University
. this QUANTITATIVE METHODS-I  
contains previous year solved papers plus faculty important questions and answers specially for PERIYAR UNIVERSITY .questions and answers are specially design specially for PERIYAR UNIVERSITY students .

 

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IMN203: QUANTITATIVE METHODS-I
Module-I: Linear Programming:
Basic concept;Structure of Linear Programming Model; Application areas of Linear
Programming; General Mathematical Model of Linear Programming Problem; Guidelines on Linear Programming Model Formulation; Examples of LP Model Formulation in variousfunctional areas of management; Graphical Solution Method of LP Problems;The Simplex Method( Maximization Case; Minimization Case-Two Phase Method & Big M Method).

 Module-II: Transportation Problem:
Mathematical Model of Transportation Problem; The Transporation Algorithm; Methods for Finding Initial Solution (North-West Corner Method, Least Cost Method, Vogel’s Approximation); Test of Optimality- MODI Method (Transportation Algorithm).


Module-III: Assignment Problem:
Mathematical Model of Assignment Problem;Solution Methods of Assignment ProblemHungerian Method for solving Assignment Problem; Variations in the Assignment ProblemMultiple Optimal solutions, Maximization Case in Assignment Problem, Unbalanced Assignment Problem, Restrictions on Assignments.


Module-IV: Decision Theory and Decision Tree:
Steps of Decision making Process; Types of Decision Making Environment; Decision Making under Uncertainity(Optimism Criterion, Pessimism Criterion, Equal Probabilities criterion, Coefficient of Optimism Criterion, Regrate Criterion); Decision Tree Analysis, Decision Making with Utilities.

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