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Overview

Optimization is the most important sub area of the discipline Operations Research. Optimization problems arise in all walks of human activity- particularly in engineering, business, finance and economics. The simplest optimization problems are linear in nature which may be subject to a set of linear constraints. This course will equip the student with the expertise to mathematically model real life optimization problems as Linear Programming (Optimization) Problems and subsequently educate the student to solve these models with the help of the available methods.

INTENDED AUDIENCE: Any student who wants to learn the basic concepts of Operations Research
PREREQUISITES: Nil
INDUSTRY SUPPORT: All industries who have to minimize cost of production or maximum output

Syllabus

COURSE LAYOUT

Week 1: Introduction to OR Models, More OR Models, Graphical Method for LPP, Convex sets, Simplex Method
Week 2: Big M Method, Two Phase, Multiple solutions of LPP, Unbounded solution of LPP, Infeasible solution of LPP
Week 3: Revised Simplex Method, Case studies and Exercises-I, Case studies and Exercises-II, Case studies andExercises - III, Primal Dual Construction
Week 4: Weak Duality Theorem, More Duality Theorems, Primal-Dual relationship of solutions, Dual Simplex Method, Sensitivity Analysis-I
Week 5: Sensitivity Analysis-II, Case studies and Exercises - I, Case studies and Exercises - II, Integer Programming Goal Programming
Week 6: Multi-Objective Programming, Dynamic Programming, Transportation Problem, Assignment Problem, Case studies and,Exercises
Week 7: Processing n Jobs on Two Machines, Processing n Jobs through Three Machines, Processing two jobs through m machines, Processing n jobs through m machines, Case studies and Exercises
Week 8: Two Person Zero-Sum Game,Theorems of Game Theory, Solution of Mixed Strategy Games, Linear Programming method for solving games, Case studies and Exercises

Taught by

Prof. Kusum Deep

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