At the end of this course, the students; 1) Have the ability to understand the basic concepts and principles of linear programming, 2) Have the ability to apply operational research methods to solve the decison models, 3) Have the ability to use the related softwares and to interpret the results obtained.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Discrete Probability Models of Reliability Engineering, Probability Density Functions used to Calculate Reliability, Mixed Distribution and Combined Effects Models, Complex Systems Design and Analysis, Optimal Design Methods for Systems, Distributions of Sample Statistics and Their use in Constructing Confidence Intervals on Reliabilities, Point an Interval Estimates for the Exponential, Bayesian Point and Interval Estimates for Exponential Binomial, Geometric and Poisson Distribution, Markov Models for Repairable Systems Reliability, Renewal Theory.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Methodology of Operations Research
2nd Week
Decision Making and Decision Models
3rd Week
Generic Form of Linear Decision Model, Basic Operations and Concepts
4th Week
Basics of Linear Programming and Solution Approaches
5th Week
Basics of Simplex Algorithm
6th Week
Operations of Simplex Algorithm
7th Week
Big M and Two Phase Simplex Algorithms
8th Week
Midterm Exam
9th Week
Duality in Linear Programming
10th Week
Dual Simplex Algorithm
11th Week
Best Post-Solution Analysis
12th Week
Sensitivity Analysis
13th Week
Transportation Model and Solution Approaches
14th Week
Assignment Model
RECOMENDED OR REQUIRED READING
Reference Book: Winston, W.L. (1994) Operations Research: Applications and Algorithms, Duxbury Press. Additional Resources: Tam, C.M., Tong, T.K.L. (2007) Decision Making and Operations Research Techniques for Construction Management, City University of Hong Kong Press.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Discussion,Presentation,Questions/Answers
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
30
Assignment
3
30
Total(%)
60
Contribution of In-term Studies to Overall Grade(%)
60
Contribution of Final Examination to Overall Grade(%)
40
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
Individual or group work
Preparation for Final exam
1
35
35
Course hours
14
3
42
Preparation for Midterm exam
1
45
45
Laboratory (including preparation)
Final exam
1
2
2
Homework
3
4
12
Total Workload
138
Total Workload / 30
4,6
ECTS Credits of the Course
5
LANGUAGE OF INSTRUCTION
English
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
