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MTH601 : Operations Research

Course Overview

Course Synopsis

This course presents the principles and techniques for solving Decision-making problems in the industry using Mathematical Models. It is the science of planning and executing operations to make the most economical use of resources available, also known as Management Science. The operation can be as simple as making a cup a tea as complicated as planning the movement of a fleet of tankers around the world. The techniques include Decision Analysis, Linear Programming, Transportation model, Assignment Model, Network Model, and Forecasting. The course emphasizes the process of model development and solution analysis.

Course Learning Outcomes

By the end of the course, students should be able:

  • To formulate a decision-making problem and apply the method of depicting a series of decisions and outcomes by decision trees.
  • To formulate the problems into mathematical model and apply the quantitative methods (graphical method and simplex method) for maximization and minimization problems
  • To formulate the transportation and assignment problems and apply the transportation simplex and Hungarian methods.
  • To define the concept of network analysis, develop the network diagram and perform network analysis.
  • To identify different types of forecast, to measure forecast accuracy and apply time-series forecasting models

Course Calendar

An overview1Handout1-5
OR Process2Handout6-8
OR Techniques and Applications3Handout9-17
Fundamental Concepts and Applications4Handout18-20
Construction of Networks5Handout21-24
Activities,Times and Floats6Handout25-32
To Find Critical Path7Handout33-34
To Find Critical Path8Handout35-37
CPM Model and PERT Model9Handout38-42
Assignment No 1
Resource Leveling10Handout43-44
Inventory Cost and Economic Order Quantities11Handout45-47
Purchasing Model and no Shortages12Handout48-49
Purchasing Model with Shortages13Handout50-54
Maunfacturing Model with no Shortages14Handout55-56
Manufacturing Model with Shortages15Handout57-59
Graded Disscussion Board No 1
Revision and Analysis16Handout60-70
Introduction to Linear Programming17Handout71-76
Formulation of LP Problems18Handout77
Formulation Exercises19Handout78-82
Solution of LP Problems20Handout83-105
Quiz No 1
Solution of LP Problems:Simplex Method21Handout106-111
Artificial Variables Techniques:Big M Method22Handout112-122
Mid Term exams
Big M Method:Examples23Handout123-129
Artificial Variables Techniques:Two Phase method24Handout130-135
Variant of Simplex Method25Handout136
Variant of Simplex Method:Degeneracy26Handout137-139
Variant of Simplex Method:Various Form of Solutions27Handout140-144
Variants of Simplex Method28Handout145-151
Duality Theory29Handout152-157
Post Optimality Analysis30Handout158-161
Graded Disscussion Board No 2
Transportation Models,Finding Initial Basic Feasible Solution31Handout162-165
Vogels approximation method32Handout166-172
Optimal Solution of Transportation Problems33Handout173-179
Examples on Transportation Problems34Handout180-192
Introduction to Assignment Problems and their Solutions36Handout199-203
Solution to Assignment Problem,Hungarian Algorithm37Handout204-222
Assignment No 2
Single Channel Infinite Population39Handout232-242
Replacment of Items with Gradual Deterioration40Handout243-247
Items Detoriating and Failing41Handout248-256
Quiz No 2
Basic Concepts and Development42Handout257-260
Solution of Dynamic Programming Problems43Handout261-270
Sequencing,Game Theory,Markov Chain,Integer Programming,Non Linear Programming44Handout271-277
Summing and Close Up45Handouts
Final Term Exams
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