QUANTITATIVE TECHNIQUES

Goal: This course is designed to provide the student with quantitative techniques for management decisions.

GENERAL OBJECTIVES: On completion of this course the student should be able to:

1.0 Understand decision analyses.

2.0 Understand Operational Research Methodology today.

3.0 Understand modeling.

4.0 Understand the process of single stage decision theory.

5.0 Understand the process of multi-stage decisions theory.

6.0 Understand Inventory Control and Production Model.

7.0 Know Queuing Theory.

8.0 Understand Simulation.

9.0 Understand Linear Programming.

10.0 Understand Special Purpose Algorithm: Transportation, Assignment and Branch-and-Bond-method.

11.0 Understand PERT, SPM and Network Analysis.

1.1 Define the concept of analysis.

1.2 Define decision making.

1.3 Identify decision situation.

1.4 Explain decision making process.

1.5 Explain scientific approach to decision making.

Define and explain decision, decision situation, process and analysis.

2.1 Define an operation.

2.2 Explain concept of operational research.

2.3 Explain basic structures of or for decision making process.

2.4 Explain O.R. stage in developing countries, (2.5) Solve O.R. type problems.

Define and explain O.R., its characteristics, structure and operational stages.

3.1 Explain the nature of models.

3.2 Explain the uses of models.

3.3 Identify advantages and disadvantages of models.

3.4 Explain the process of modeling.

3.5 Classify models e.g. ICONIC, analogue, symbolic/mathematical etc.

3.5 Identify advantages and limitations of mathematical models.

Prototypes in O.R.

Define and explain modeling.

Explain the process and types of modeling.

Explain various prototype in O.R. to date.

Carry out visitations’ to places where models are located e.g. libraries.

4.1 Explain decision under certainty.

4.2 Explain decision under risk.

4.3 Explain decision under uncertainty.

Solve case studies on decision under risk and uncertainty.

5.1 Identify multi-stage decision situation.

5.2 Formulate problems into decision tree.

5.3 Solve and interpret decision tree problems.

Solve case studies on decision three problems.

6.1 Derive inventory model under non-instantaneous supply.

6.2 Derive EOQ model under non-instantaneous supply.

6.3 Solve EOQ problems under instantaneous supply.

6.4 Derive inventory model under non-instantaneous supply.

6.5 Derive EOQ model under non-instantaneous supply

6.6 Solve EOQ problems under non-instantaneous supply.

Assign and solve problems and/or case studies on Inventory problems.

Arrange visitation to Company stores and observe stock taking.

7.1 Explain the concept of queuing (waiting lines).

7.2 Explain queuing objectives and cost behaviour.

7.3 Explain the assumptions of queuing model.

7.4 Formulate single server model.

Explain cost analysis in queuing.

Explain Queuing problems and solve case studies on queue problems.

Carry out visitations to banks hospitals and traffic point where there are queues.

8.1 Explain general nature of simulation.

8.2 Identify the advantages and limitations of simulation.

8.3 Explain the Monte Carlo simulation method.

8.4 Apply simulation to solving real life cost analysis problems.

Explain and solve case studies on simulation problems.

9.1 Define Linear Programming.

9.2 Identify the major requirements of L.P. problems.

9.3 Explain allocation problems.

9.4 Identify the properties of LP

9.5 Explain the assumptions of LP model.

9.6 Formulate LP modelmaximization and minimization.

9.7 Solve LP problems:-

- Graphical approach (maximization and minimization).

- Simplex Method (maximization and minimization).

9.8 Explain the concept of duality in L.P.

9.9 Solve dual L.P. problems.

Explain L.P problems.

Solve case studies on L.P. problems.

10.1 Explain the nature of transportation problems.

10.2 Explain the characteristics of transportation problems.

10.3 Formulate transportation models.

10.4 Solve transportation problems.

10.5 Explain the concept of MODI Method.

10.6 Explain assignment method.

10.7 Explain Branch-and-Bond method of assignment problem.

10.8 Distinguish between assignment problem and L.P. problem.

10.9 Identify the difference between assignment and transportation problem.

10.10 Formulate assignment model.

10.11 Solve assignment problems using assignment model.

10.12 Solve transportation problems using L.P. method.

Explain transportation problems.

Solve case studies on transportation problems.

11.1 Define PERT.

11.2 Explain the general nature of network analysis and project scheduling.

11.3 Distinguish between repetitive and non-repetitive operations.

11.4 Draw simple project network analyzing activities and the events.

11.5 Sketch several activities showing beginning and ending events.

11.6 Explain the concept of TE, TL, Slack and Negative Slack.

11.7 Explain CBM .

11.8 Construct a PERT network and compute TE, TL, and S for all the events.

11.9 Explain project crasing techniques.

11.10 Construct a network scheduling for problems with resource limitations.

Explain with graphic illustration, network analysis and project scheduling.

Solve case studies on network analysis problems.

Construct network for problems with limited resources.