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Computer Based Optimization Methods (Statistics/Applied OR)
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Course Name
MCA (Master of Computer Application)
Subject Code MC0079 (Computer Based Optimization Methods (Statistics/Applied OR))
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PART - A
PART - B
PART - C
Computer Based Optimization Methods (Statistics/Applied OR) Syllabus.
Part 1 Operations Research: The Science towards Excellence
Introduction; Scope of Operations Research (OR); The significant features of
OR; Phases of operations Research; Methodology of Operations Research; The
Structure of Mathematical Model
Part 2 Linear Programming
Introduction; Linear Programming; Some basic definitions; Graphical Methods
to Solve the LP
Part 3 The Simplex Method
Introduction; The Standard form of LPP; Solution of the LPP – Simplex
Method; The Simplex Algorithm, Flowchart and C/C++ Programs; Penalty cost Method
or Big-M Methods; Two Phase Method; Duality Concept; Sensitivity Analysis
Part 4 Transportation Problems
Introduction; Mathematical Formulation of Transportation Problem; Methods of
finding Initial Basic Feasible Solution; Modified Distribution Method Algorithm;
Degeneracy in Transportation Problem
Part 5 Assignment Problems
Introduction; Special case of Transportation Problem; Hungarian Method; Some
special cases
Part 6 Network Analysis and PERT-CPM
Introduction; Basic difference between PERT and CPM; PERT / CPM Network
components and precedence relationships; Critical path Calculations;
Determination of critical path; Determination of Floats; Project Management –
PERT
Part 7 Queuing Theory Models
Introduction; Queuing Theory; Analysis of a Queuing Process; General
Structure of Queuing System; Mathematical Analysis of Queuing Process;
Poisson-Exponential Single Server Model (Infinite Population); Multiple Service
Channels; Erlang Family of Distribution of Service Times; Finite Queuing Models
Part 8 Integer Programming Problem
Introduction; All and Mixed IPP; Gomory‘s all IPP Method; Construction of
Gomory‘s Constraints; All IPP algorithm; The Branch and bound technique
Part 9 Game Theory Models
Introduction; Competitive Games and Strategies; Maximin – Minimax Principle
and Saddle Point; Dominance; Graphical Method
Part 10 Simulation
Introduction; Process of Simulation; Simulation Procedure; Random Numbers
Allocation; Some Miscellaneous Example
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