Information Package
baskent.edu.tr

Ph.D. on Business Administration

MAND619

LINEAR PROGRAMMING

Course Code
MAND619
Semester
-
Theory+Practice
3 + 0
ECTS
15
Course TypeElective Course
Course LevelDoctorate Of Science
Year of Study-
Semester-
ECTS15
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Use various linear programming methods to make good decisions.
  2. Develop the infrastructure necessary to distinguish the best model appropriate for a specific decision making situation.
  3. Develop skills for formulating mathematical models of real life business problems.
  4. Use specialized software available to solve the models.
  5. Develop skills for interpreting the results of the computer outputs.
  6. Demonstrate the ability to approach different kinds of decision making situations analytically.
  7. Develop analytical skills in structuring and analysis of business decision problems that display characteristics of linearity.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsMAND618 MANAGERIAL DECISION MAKING
Course DescriptionThe field of linear programming aims to solve organizations' problems via mathematical expressions. This course includes quantifying problems faced by firms and producing optimal solutions for those quantified problems. mathematical expression
Course Contents
WEEK TOPICS
1st Week Fundamentals of Linear Programming
2nd Week Formulating the Linear Programming Models: Business Applicatiions
3rd Week Solving the Linear Programming Problems: Graphical and Computer Methods
4th Week Spacial Types of Linear Programming Problems
5th Week Sensitivity Analysis of the Objective Function Coefficients, Ranges of Optimality and Reduced Costs
6th Week Sensitivity Analysis of the Right-Hand Side Values (Shadow Prices) and Ranges of Validity
7th Week Use of Sensitivity Analysis in Decision Making with Managerial Applications
8th Week Midterm
9th Week Network Flow Formulations (the Transportation, the Transshipment and Assignment Models)
10th Week Network Flow Formulations (the Maximum Flow, Minimum Spanning Tree, Shortest Route, Traveling Salesman Models)
11th Week Goal Programming Formulations
12th Week Integer Linear Programming Formulations with General Integer Variables
13th Week Integer Linear Programming Formulations with Binary Decision Variables
14th Week Business Applications
15th Week General Review
Recommended or Required ReadingTaylor, Bernard W. 2012. Introduction to Management Science, 11.thed., Pearson.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Quiz 1 20
Total(%) 50
Contribution of In-term Studies to Overall Grade(%) 50
Contribution of Final Examination to Overall Grade(%) 50
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz 2 8 16
Individual or group work 13 6 78
Preparation for Final exam 1 170 170
Course hours 14 3 42
Preparation for Midterm exam 1 80 80
Laboratory (including preparation) 1 40 40
Final exam 1 2 2
Homework 4 4 16
Article
Total Work Load446
Total Work Load / 30 (h)14.86
ECTS Credit of the Course15
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4 LO5 LO6 LO7
K1 X X X X
K2 X X X X X
K3 X X X X X
K4
K5 X X X X X
K6
K7
K8 X X
K9
K10
K11 X