204 Decision Science | MBA MCQs | SPPU | DS

CHAPTER 1 – 

 1.1 Introduction: Importance of Decision Sciences & Role of quantitative techniques in decision making.

1.2 Assignment Models: Concept, Flood’s Technique/ Hungarian Method, applications including restricted & multiple assignments.

1.3 Transportation Models: Concept, Formulation, Problem types: Balanced, unbalanced, Minimization, Maximization Basic initial solution using North West Corner, Least Cost & VAM, Optimal Solution using MODI.

 Decision Science | Chapter 1 | Part 1

 Decision Science | Chapter 1 | Part 2

 Decision Science | Chapter 1 | Part 3

 Decision Science | Chapter 1 | Part 4

 Decision Science | Chapter 1 | Part 5

CHAPTER 2 - 

 2.1 Linear Programming: Concept, Formulation & Graphical Solution

2.2 Markov Chains & Simulation Techniques: Markov chains: Applications related to management functional areas, Implications of Steady state Probabilities, Decision making based on the inferences Monte Carlo Simulation, scope and limitations.

 Decision Science | Chapter 2 | Part 1

 Decision Science | Chapter 2 | Part 2

 Decision Science | Chapter 2 | Part 3

 Decision Science | Chapter 2 | Part 4

 Decision Science | Chapter 2 | Part 5

CHAPTER 3 - 

3.1 Decision Theory: Concept, Decision under risk (EMV)& uncertainty

3.2 Game Theory: Concept,2 by 2 zero sum game with dominance, Pure & Mixed Strategy

3.3 Queuing Theory: Concept, Single Server ( M/M/I , Infinite, FIFO) and Multi Server (M/M/C , Infinite, FIFO)

 Decision Science | Chapter 3 | Part 1

 Decision Science| Chapter 3 | Part 2

 Decision Science | Chapter 3 | Part 3

 Decision Science | Chapter 3 | Part 4

 Decision Science | Chapter 3 | Part 5

CHAPTER 4 – 

4.1 CPM & PERT: Concept, Drawing network, identifying critical path

Network Calculations: Calculating EST, LST, EFT, LFT, Slack & probability of project completion

4.2 Sequencing problems: Introduction, Problems involving n jobs- 2 machines, n jobs- 3 machines & n jobs-m machines; Comparison of priority sequencing rules.

 Decision Science | Chapter 4 | Part 1

 Decision Science | Chapter 4 | Part 2

 Decision Science | Chapter 4 | Part 3

 Decision Science | Chapter 4 | Part 4

 Decision Science | Chapter 4 | Part 5

CHAPTER 5 –

5.1 Probability: Concept, Addition, Conditional Probability theorem based decision making, (Numerical based on functional areas of business expected).

5.2 Probability Distributions: Normal, Binomial. Interval estimation, standard errors of estimation.

 Decision Science | Chapter 5 | Part 1

 Decision Science | Chapter 5 | Part 2

 Decision Science | Chapter 5 | Part 3

 Decision Science | Chapter 5 | Part 4

 Decision Science | Chapter 5 | Part 5