SlideShare a Scribd company logo
1 of 8
PUNJAB COLLEGE OF TECHNICAL EDUCATION,
            LUDHIANA




                        COURSE MODULE
                    OPERATIONS RESEARCH
                          [ BC- 504(N2) ]



Max. Marks 100                                      Internal
Assessment - 40
                                              External Assessment -
60




Instruction for paper setter

      The question paper will consist of two sections A and B.

      Sections B will have Six questions and will carry 10 marks
       each. Section A will have 10 short answer type questions,
       which will cover the entire syllabus uniformly and will carry
       20 marks in all.




Instructions for Candidates

      Candidates are required to attempt four questions from
       section B and the entire section A.

      Use of non-programmable scientific calculator is allowed.
Syllabus

                         OPERATION RESEARCH

                                BC-504 (N2)

Max Marks: 100                                            Internal
Assessment: 40

                                                       External
                                                       Assessment: 60

                         Instructions for paper setter

The question paper will consist of two sections A and B.
Sections B will have Six questions and will carry 10 marks each.
Section A will have 10 short answer type questions, which will
cover the entire syllabus uniformly and will carry 20 marks in
all.

                         Instructions for Candidates

Candidates are required to attempt four questions from section
B and the entire section A. Use of non-programmable scientific
calculator is allowed

Origin & development of O.R., Nature & Characteristics
features of O.R., Models & Modeling in Operation Research.
Methodology of O.R., General methods for solving O.R. Models,
O.R. & Decision making, Application, Use & Limitations of O.R.

Linear Programming: formulation, Graphical, Big Method &
Simplex Method, Duality in L.P.: Conversion of Primal to Dual
only

Transportation   Problems:   Test     for   Optimality,    Degeneracy   in
Transportation   Problems.    Unbalanced     Transportation,
Assignment Problems, Traveling Salesman Problem.

Decision Making : Decision Making Environment, Decision under
uncertainty, Decision under risk, Decision tree Analysis.

Integer Programming and Dynamic Programming: Concept and
Advantages only.

REFERENCES:

1.Kanti Sawrup, P.K. Gupta and Manmohan, "Operations
Research", Sultan Chand & Sons, Seventh Ed.1994.
2.S.D. Sharma, Operations Research", Kedar Nath Ram Nath
and Co. Meerut, Tenth Ed. 1992.
Important Guidelines


   1. ATTENDANCE CRITERIA – 75% (NO COMPROMISES!!)
   2. YOU ARE EXPECTED TO BE IN CLASS ON/BEFORE SCHEDULED
      TIME. AFTER THAT YOU CAN ATTEND THE CLASS BUT WOULD
      NOT BE AWARDED ATTENDANCE. NO EXCUSES FOR BEING LATE
      WILL BE ENTERTAINED.
   3. MAKE SURE YOU ARE NOT ABSENT ON PRESENTATION DAY OR
      ACTIVITY DAY OR TESTS. ZERO MARKS WOULD BE AWARDED TO
      ABSENTEES. YOU’LL BE INFORMED WELL IN ADVANCE ABOUT
      THE IMPORTANT DEADLINES.
   4. DO NOT COPY ASSIGNMENTS. ALL THE COPIED ASSIGNMENTS
      AND       MASTER    ASSIGNMENT      WOULD      BE   STRAIGHT      AWAY
      CANCELLED & AWARDED ZERO MARKS.



Following are the parameters along with weight-age for the final calculation of
Internal.

                         Internal Evaluation Breakup



         Marks                                 Parameters

            15                 MID SEMESTER EXAMINATION [MSE]

            5                               PRESENTATION

            10                   TESTS [First Hourly, Second Hourly]

            10                               ASSIGNMENTS
Course Breakup
Class: BCA-III-D                                                 Lectures: 47

Subject: Operations Research                                     No. of Tests: 3

Code: BC- 504(N2)                                                Assignments: 3

Teacher: Kapil Prashar [KP]



Lecture     Date    Contents of Lecture
                                                                         Tests     Assignment
No.
      1.            Introduction to Operation Research:

                    Origin & Development of O. R.

                    Meaning & Definitions of O.R.

                    Nature and Characteristics of O. R.

      2.            Introduction to O.R.

                    Various Models of O. R.
                    Methodology of O.R.
      3.            Introduction to Operation Research:

                     O. R. And Decision making
                     Applications of O. R.
                     Uses and Limitations of O.R.
      4.            Assignment Problems

                        ♦     Meaning of Assignment Problems
                        ♦     Formulation of Assignment Matrix
                        •     Hungarian Method
      5.                •     Application of Hungarian Method.                     ASSG 1


      6.                •     Maximization and Unbalanced case in
                              Assignment Problems
      7.                •     Air crew Assignment Problems

      8.            Assignment Problem

                        •     Travelling Salesman Problem
      9.                •     Tutorial/ Problems

      10.           Introduction to Transportation Model

                        •     Feasible solution
                        •     Basic feasible solution
                        •     Optimal solution
                        •     Balanced & Unbalanced Transportation
                              Model
11.   Solving of a Balanced Transportation Problem:              ASSG 2

         Step I : Make a Transportation Model

         Step II : To find a basic feasible Solution:

         o       North West Corner Method
         o       Lowest Cost Entry Method.
         •       Vogel’s Approximation Method (VAM)
12.      •       Step II: Finding a basic feasible solution.

13.                    Transportation Problem

             •     Step III: Optimality Test- MODI Method
14.

15.
             MODIFIED DISTRIBUTION OPTIMALITY TEST
16.

17.

18.   Transportation Problem

         •       Optimality Test- STEPPING STONE METHOD


19.   Transportation Problem

          • Unbalanced Problem
          • Profit Maximization Problem
20.   Linear Programming

      1. Introduction
      2. Assumptions of Linear Programming
         • Advantages of Linear Programming
         • Limitations of Linear Programming


21.      •       Applications of Linear Programming
         •       Formulation of the LPP
22.      •       Formulation of the LPP

23.      •       Formulation of the problem- Numericals
         •       Graphical Method of LPP
24.      •       Graphical Method of LPP –Numericals

         Tutorial/ Problems

25.   Linear Programming

         •       Basic terms used in Simplex method: Slack
                 variable, Surplus variable, Basic sol., Basic
                 feasible sol, Optimum sol.
         •       Construction of standard form of LPP
26.      •       Iterations                                      ASSG 3

27.      •       Iterations
28.      •   Iterations

29.   Simplex method for greater than equal to
      constraints:

         • Surplus variables
         • Artificial variables
         • Introduction to Big M method
30.   Greater than equal to constraints using Big M
      method

31.   Greater than equal to constraints using Big M
      method

32.   Mixed constraints

33.   Tutorial/ Problems

34.   Special cases in applying simplex method

          • Degeneracy
          • Unbounded problems
          • Infeasible problems
          • Redundancy problem
35.   Linear Programming (Duality)

          • Construction of dual
36.   Linear Programming (Duality)

         • Problems of Duality
37.   Decision Making

            Steps in decision making
            Types of Decision Making Environment


38.   Decision Making

             Decision making in Uncertainty
                 o Maximax & Minimin Criteria
                 o Maximin & Minimax Criteria
39.   Decision Making

             Criterion of realism
             Criterion of regret
                  o Equally Likely
40.   Decision Making

         •    Under Risk
                 o EMV
41.   Decision Making

         •    Under Risk
                 o EOL
42.   Decision Making

         •   Under Risk
o EVPI
43.   Decision Making

         •   Decision Tree Analysis


44.   Integer Programming

            Need of integer programming
            Types of integer programming


45.   Tutorial/ Problems

46.   Dynamic Programming

         • Basic Concept
         • Need of Dynamic Programming
47.   Dynamic Programming

         •   Advantages
         •   Nature, Features
         •   Usages

More Related Content

Viewers also liked

Mech vii-operation research [06 me74]-notes
Mech vii-operation research [06 me74]-notesMech vii-operation research [06 me74]-notes
Mech vii-operation research [06 me74]-notes
Mallikarjunaswamy Swamy
 
Simplex method - Maximisation Case
Simplex method - Maximisation CaseSimplex method - Maximisation Case
Simplex method - Maximisation Case
Joseph Konnully
 
Linear programming - Model formulation, Graphical Method
Linear programming  - Model formulation, Graphical MethodLinear programming  - Model formulation, Graphical Method
Linear programming - Model formulation, Graphical Method
Joseph Konnully
 
QUEUING THEORY
QUEUING THEORYQUEUING THEORY
QUEUING THEORY
avtarsingh
 
Basic Concept Of Probability
Basic Concept Of ProbabilityBasic Concept Of Probability
Basic Concept Of Probability
guest45a926
 

Viewers also liked (20)

Mech vii-operation research [06 me74]-notes
Mech vii-operation research [06 me74]-notesMech vii-operation research [06 me74]-notes
Mech vii-operation research [06 me74]-notes
 
OR 14 15-unit_2
OR 14 15-unit_2OR 14 15-unit_2
OR 14 15-unit_2
 
OR 14 15-unit_1
OR 14 15-unit_1OR 14 15-unit_1
OR 14 15-unit_1
 
Unit 6 inventory
Unit 6 inventoryUnit 6 inventory
Unit 6 inventory
 
OR Unit 5 queuing theory
OR Unit 5 queuing theoryOR Unit 5 queuing theory
OR Unit 5 queuing theory
 
Simplex method - Maximisation Case
Simplex method - Maximisation CaseSimplex method - Maximisation Case
Simplex method - Maximisation Case
 
Operation research
Operation research Operation research
Operation research
 
Linear programming ppt
Linear programming pptLinear programming ppt
Linear programming ppt
 
Linear programing
Linear programingLinear programing
Linear programing
 
Operations research - an overview
Operations research -  an overviewOperations research -  an overview
Operations research - an overview
 
Queuing theory
Queuing theoryQueuing theory
Queuing theory
 
Linear Programming
Linear ProgrammingLinear Programming
Linear Programming
 
Queuing Theory - Operation Research
Queuing Theory - Operation ResearchQueuing Theory - Operation Research
Queuing Theory - Operation Research
 
Linear programming - Model formulation, Graphical Method
Linear programming  - Model formulation, Graphical MethodLinear programming  - Model formulation, Graphical Method
Linear programming - Model formulation, Graphical Method
 
QUEUING THEORY
QUEUING THEORYQUEUING THEORY
QUEUING THEORY
 
Basic Concept Of Probability
Basic Concept Of ProbabilityBasic Concept Of Probability
Basic Concept Of Probability
 
Presentation On Motivation
Presentation On MotivationPresentation On Motivation
Presentation On Motivation
 
Queueing theory
Queueing theoryQueueing theory
Queueing theory
 
Operation research complete
Operation research completeOperation research complete
Operation research complete
 
Theory of queuing systems
Theory of queuing systemsTheory of queuing systems
Theory of queuing systems
 

Similar to BC 504-Operation Research

Structural Component Design Optimization for Additive Manufacture
Structural Component Design Optimization for Additive ManufactureStructural Component Design Optimization for Additive Manufacture
Structural Component Design Optimization for Additive Manufacture
Altair
 
Student copybca sem3-se
Student copybca sem3-seStudent copybca sem3-se
Student copybca sem3-se
anilmanu2001
 
Aqt instructor-notes-final
Aqt instructor-notes-finalAqt instructor-notes-final
Aqt instructor-notes-final
waheedjan
 
ASS_SDM2012_Ali
ASS_SDM2012_AliASS_SDM2012_Ali
ASS_SDM2012_Ali
MDO_Lab
 
E:\Cheenu Pcte\Course Module\Cost Accounting
E:\Cheenu Pcte\Course Module\Cost Accounting E:\Cheenu Pcte\Course Module\Cost Accounting
E:\Cheenu Pcte\Course Module\Cost Accounting
cheenugoel
 
AIAA-SDM-SequentialSampling-2012
AIAA-SDM-SequentialSampling-2012AIAA-SDM-SequentialSampling-2012
AIAA-SDM-SequentialSampling-2012
OptiModel
 
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
hani_abdeen
 

Similar to BC 504-Operation Research (20)

Structural Component Design Optimization for Additive Manufacture
Structural Component Design Optimization for Additive ManufactureStructural Component Design Optimization for Additive Manufacture
Structural Component Design Optimization for Additive Manufacture
 
Student copybca sem3-se
Student copybca sem3-seStudent copybca sem3-se
Student copybca sem3-se
 
Aqt instructor-notes-final
Aqt instructor-notes-finalAqt instructor-notes-final
Aqt instructor-notes-final
 
VSS_CH352_BTech_EO_23-24_Module-1_VSS.ppt
VSS_CH352_BTech_EO_23-24_Module-1_VSS.pptVSS_CH352_BTech_EO_23-24_Module-1_VSS.ppt
VSS_CH352_BTech_EO_23-24_Module-1_VSS.ppt
 
ASS_SDM2012_Ali
ASS_SDM2012_AliASS_SDM2012_Ali
ASS_SDM2012_Ali
 
E:\Cheenu Pcte\Course Module\Cost Accounting
E:\Cheenu Pcte\Course Module\Cost Accounting E:\Cheenu Pcte\Course Module\Cost Accounting
E:\Cheenu Pcte\Course Module\Cost Accounting
 
Lecture 1 Chapter 1 Introduction to OR.pdf
Lecture 1 Chapter 1 Introduction to OR.pdfLecture 1 Chapter 1 Introduction to OR.pdf
Lecture 1 Chapter 1 Introduction to OR.pdf
 
OR chapter 1.pdf
OR chapter 1.pdfOR chapter 1.pdf
OR chapter 1.pdf
 
Pedbesy
PedbesyPedbesy
Pedbesy
 
Introduction.ppt
Introduction.pptIntroduction.ppt
Introduction.ppt
 
Comparing Incremental Learning Strategies for Convolutional Neural Networks
Comparing Incremental Learning Strategies for Convolutional Neural NetworksComparing Incremental Learning Strategies for Convolutional Neural Networks
Comparing Incremental Learning Strategies for Convolutional Neural Networks
 
Operations research lpp
Operations research lppOperations research lpp
Operations research lpp
 
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual RepresentationsA Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
 
Presentation 2 fyp (043362)
Presentation 2 fyp (043362)Presentation 2 fyp (043362)
Presentation 2 fyp (043362)
 
AIAA-SDM-SequentialSampling-2012
AIAA-SDM-SequentialSampling-2012AIAA-SDM-SequentialSampling-2012
AIAA-SDM-SequentialSampling-2012
 
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
Multi-Objective Optimization in Rule-based Design Space Exploration (ASE 2014)
 
OOSE Unit 5 PPT.ppt
OOSE Unit 5 PPT.pptOOSE Unit 5 PPT.ppt
OOSE Unit 5 PPT.ppt
 
Xmba 296t mentor handbook rev 3
Xmba 296t mentor handbook rev 3Xmba 296t mentor handbook rev 3
Xmba 296t mentor handbook rev 3
 
Oose unit 5 ppt
Oose unit 5 pptOose unit 5 ppt
Oose unit 5 ppt
 
Lec 01 introduction
Lec 01   introductionLec 01   introduction
Lec 01 introduction
 

Recently uploaded

The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
heathfieldcps1
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
QucHHunhnh
 

Recently uploaded (20)

Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptx
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Fostering Friendships - Enhancing Social Bonds in the Classroom
Fostering Friendships - Enhancing Social Bonds  in the ClassroomFostering Friendships - Enhancing Social Bonds  in the Classroom
Fostering Friendships - Enhancing Social Bonds in the Classroom
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structure
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POS
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxSKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 

BC 504-Operation Research

  • 1. PUNJAB COLLEGE OF TECHNICAL EDUCATION, LUDHIANA COURSE MODULE OPERATIONS RESEARCH [ BC- 504(N2) ] Max. Marks 100 Internal Assessment - 40 External Assessment - 60 Instruction for paper setter  The question paper will consist of two sections A and B.  Sections B will have Six questions and will carry 10 marks each. Section A will have 10 short answer type questions, which will cover the entire syllabus uniformly and will carry 20 marks in all. Instructions for Candidates  Candidates are required to attempt four questions from section B and the entire section A.  Use of non-programmable scientific calculator is allowed.
  • 2. Syllabus OPERATION RESEARCH BC-504 (N2) Max Marks: 100 Internal Assessment: 40 External Assessment: 60 Instructions for paper setter The question paper will consist of two sections A and B. Sections B will have Six questions and will carry 10 marks each. Section A will have 10 short answer type questions, which will cover the entire syllabus uniformly and will carry 20 marks in all. Instructions for Candidates Candidates are required to attempt four questions from section B and the entire section A. Use of non-programmable scientific calculator is allowed Origin & development of O.R., Nature & Characteristics features of O.R., Models & Modeling in Operation Research. Methodology of O.R., General methods for solving O.R. Models, O.R. & Decision making, Application, Use & Limitations of O.R. Linear Programming: formulation, Graphical, Big Method & Simplex Method, Duality in L.P.: Conversion of Primal to Dual only Transportation Problems: Test for Optimality, Degeneracy in Transportation Problems. Unbalanced Transportation, Assignment Problems, Traveling Salesman Problem. Decision Making : Decision Making Environment, Decision under uncertainty, Decision under risk, Decision tree Analysis. Integer Programming and Dynamic Programming: Concept and Advantages only. REFERENCES: 1.Kanti Sawrup, P.K. Gupta and Manmohan, "Operations Research", Sultan Chand & Sons, Seventh Ed.1994.
  • 3. 2.S.D. Sharma, Operations Research", Kedar Nath Ram Nath and Co. Meerut, Tenth Ed. 1992.
  • 4. Important Guidelines 1. ATTENDANCE CRITERIA – 75% (NO COMPROMISES!!) 2. YOU ARE EXPECTED TO BE IN CLASS ON/BEFORE SCHEDULED TIME. AFTER THAT YOU CAN ATTEND THE CLASS BUT WOULD NOT BE AWARDED ATTENDANCE. NO EXCUSES FOR BEING LATE WILL BE ENTERTAINED. 3. MAKE SURE YOU ARE NOT ABSENT ON PRESENTATION DAY OR ACTIVITY DAY OR TESTS. ZERO MARKS WOULD BE AWARDED TO ABSENTEES. YOU’LL BE INFORMED WELL IN ADVANCE ABOUT THE IMPORTANT DEADLINES. 4. DO NOT COPY ASSIGNMENTS. ALL THE COPIED ASSIGNMENTS AND MASTER ASSIGNMENT WOULD BE STRAIGHT AWAY CANCELLED & AWARDED ZERO MARKS. Following are the parameters along with weight-age for the final calculation of Internal. Internal Evaluation Breakup Marks Parameters 15 MID SEMESTER EXAMINATION [MSE] 5 PRESENTATION 10 TESTS [First Hourly, Second Hourly] 10 ASSIGNMENTS
  • 5. Course Breakup Class: BCA-III-D Lectures: 47 Subject: Operations Research No. of Tests: 3 Code: BC- 504(N2) Assignments: 3 Teacher: Kapil Prashar [KP] Lecture Date Contents of Lecture Tests Assignment No. 1. Introduction to Operation Research: Origin & Development of O. R. Meaning & Definitions of O.R. Nature and Characteristics of O. R. 2. Introduction to O.R. Various Models of O. R. Methodology of O.R. 3. Introduction to Operation Research:  O. R. And Decision making  Applications of O. R.  Uses and Limitations of O.R. 4. Assignment Problems ♦ Meaning of Assignment Problems ♦ Formulation of Assignment Matrix • Hungarian Method 5. • Application of Hungarian Method. ASSG 1 6. • Maximization and Unbalanced case in Assignment Problems 7. • Air crew Assignment Problems 8. Assignment Problem • Travelling Salesman Problem 9. • Tutorial/ Problems 10. Introduction to Transportation Model • Feasible solution • Basic feasible solution • Optimal solution • Balanced & Unbalanced Transportation Model
  • 6. 11. Solving of a Balanced Transportation Problem: ASSG 2 Step I : Make a Transportation Model Step II : To find a basic feasible Solution: o North West Corner Method o Lowest Cost Entry Method. • Vogel’s Approximation Method (VAM) 12. • Step II: Finding a basic feasible solution. 13. Transportation Problem • Step III: Optimality Test- MODI Method 14. 15. MODIFIED DISTRIBUTION OPTIMALITY TEST 16. 17. 18. Transportation Problem • Optimality Test- STEPPING STONE METHOD 19. Transportation Problem • Unbalanced Problem • Profit Maximization Problem 20. Linear Programming 1. Introduction 2. Assumptions of Linear Programming • Advantages of Linear Programming • Limitations of Linear Programming 21. • Applications of Linear Programming • Formulation of the LPP 22. • Formulation of the LPP 23. • Formulation of the problem- Numericals • Graphical Method of LPP 24. • Graphical Method of LPP –Numericals Tutorial/ Problems 25. Linear Programming • Basic terms used in Simplex method: Slack variable, Surplus variable, Basic sol., Basic feasible sol, Optimum sol. • Construction of standard form of LPP 26. • Iterations ASSG 3 27. • Iterations
  • 7. 28. • Iterations 29. Simplex method for greater than equal to constraints: • Surplus variables • Artificial variables • Introduction to Big M method 30. Greater than equal to constraints using Big M method 31. Greater than equal to constraints using Big M method 32. Mixed constraints 33. Tutorial/ Problems 34. Special cases in applying simplex method • Degeneracy • Unbounded problems • Infeasible problems • Redundancy problem 35. Linear Programming (Duality) • Construction of dual 36. Linear Programming (Duality) • Problems of Duality 37. Decision Making  Steps in decision making  Types of Decision Making Environment 38. Decision Making  Decision making in Uncertainty o Maximax & Minimin Criteria o Maximin & Minimax Criteria 39. Decision Making  Criterion of realism  Criterion of regret o Equally Likely 40. Decision Making • Under Risk o EMV 41. Decision Making • Under Risk o EOL 42. Decision Making • Under Risk
  • 8. o EVPI 43. Decision Making • Decision Tree Analysis 44. Integer Programming  Need of integer programming  Types of integer programming 45. Tutorial/ Problems 46. Dynamic Programming • Basic Concept • Need of Dynamic Programming 47. Dynamic Programming • Advantages • Nature, Features • Usages