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Operation Research Semester 6 (TE Third Year) BE Computer Engineering University of Mumbai Topics and Syllabus

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University of Mumbai Syllabus For Semester 6 (TE Third Year) Operation Research: Knowing the Syllabus is very important for the students of Semester 6 (TE Third Year). Shaalaa has also provided a list of topics that every student needs to understand.

The University of Mumbai Semester 6 (TE Third Year) Operation Research syllabus for the academic year 2021-2022 is based on the Board's guidelines. Students should read the Semester 6 (TE Third Year) Operation Research Syllabus to learn about the subject's subjects and subtopics.

Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the University of Mumbai Semester 6 (TE Third Year) Operation Research Syllabus pdf 2021-2022. They will also receive a complete practical syllabus for Semester 6 (TE Third Year) Operation Research in addition to this.

CBCGS [2018 - current]
CBGS [2014 - 2017]
Old [2000 - 2013]

University of Mumbai Semester 6 (TE Third Year) Operation Research Revised Syllabus

University of Mumbai Semester 6 (TE Third Year) Operation Research and their Unit wise marks distribution

University of Mumbai Semester 6 (TE Third Year) Operation Research Course Structure 2021-2022 With Marking Scheme

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C What Is Operations Research
CC Modeling With Linear Programming
201 Two-variable LP Model
202 Graphical LP Solution
  • Solution of a Maximization Model
  • Solution of a Minimization Model
203 Computer Solution With Solver And AMPL
  • LP solution with Excel Solver
  • LP Solution with AMPL
204 Linear Programming Applications
  • Investment
  • Product Planning and Inventory Control
  • Manpower Planning
  • Urban Development Planning
  • Blending and Refining
  • Additional LP Applications
CCC The Simplex Method And Sensitivity Analysis
301 LP Model In Equation Form
302 Transition From Graphical To Algebraic Solution
303 The Simplex Method
  • Iterative Nature of the Simplex Method
  • Computational details of the Simplex algorithm
  • Summary of the Simplex Method
304 Artificial Starting Solution
  • M-Method
  • Two-Phase Method
305 Special Cases In The Simplex Method
  • Degeneracy
  • Alternative Optima
  • Unbounded Solution
  • Infeasible Solution
306 Sensitivity Analysis
  • Graphical Sensitivity Analysis
  • Algebraic Sensitivity Analysis – Changes in the Right­hand side
  • Algebraic Sensitivity Analysis – Objective function
  • Sensitivity Analysis with Tora, Solver, and Ampl
307 Computational Issues In Linear Programming
CD Duality and Post-optimal Analysis
401 Definition Of The Dual Problem
402 Primal-dual Relationships
  • Review of Simplex Matrix Operations
  • Simplex Tableau Layout
  • Optimal Dual Solution
  • Simplex Tableau Computations
403 Economic Interpretation of Duality
  • Economic Interpretation of Dual Variables
  • Economic Interpretation of Dual Constraints
404 Additional Simplex Algorithms
  • Dual Simplex Algorithm
  • Generalized Simplex Algorithm
D Transportation Model And Its Variants
501 Definition Of The Transportation Model
502 Nontraditional Transportation Models
503 The Transportation Algorithm
  • Determination of the Starting Solution
  • Iterative Computations of the Transportation Algorithm
  • Simplex Method Explanation of the Method of Multipliers
504 The Assignment Model
  • The Hungarian Method
  • Simplex Explanation of the Hungarian Method
DC Decision Analysis
601 Decision Making Under Certainty
  • Analytic Hierarchy Process (AHP)
602 Decision Making Under Risk
  • Decision Tree-Based Expected Value Criterion
  • Variants of the Expected Value Criterion
603 Decision Under Uncertainty
DCC Stimulation Modeling
701 Monte Carlo Simulation
702 Types Of Simulation
703 Elements Of Discrete Event Simulation
  • Generic Definition of Events
  • Sampling from Probability Distributions
DCCC Nonlinear Programming Algorithms
801 Unconstrained Algorithms
  • Direct Search Method
  • Gradient Method
802 Constrained Algorithms
  • Separable Programming
  • Quadratic Programming
CM Introduction To Spreadsheet Model
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