COURSE UNIT TITLE

: LINEAR PROGRAMMING APPLICATIONS IN CLINICAL TRIALS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MIF 5014 LINEAR PROGRAMMING APPLICATIONS IN CLINICAL TRIALS ELECTIVE 2 0 0 4

Offered By

Medical Informatics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Medical Informatics

Course Objective

The objective of the course is to learn basic concepts, generalization, solution approaches, basic methods and application areas of linear programming and to gain skills regarding application of these methods in clinical problems. Besides, to formulize clinical problems as decision problems, identifying decision alternatives, and selecting the best decision alternative, and finally make economic interpretations.

Learning Outcomes of the Course Unit

1   The student should define basic concepts of the linear programming,
2   express the clinical problems as decision problems,
3   find the solution of linear decision problems with the use of operations research packages,
4   interpret the results economically,
5   suggest alternatives to optimize the objective,
6   make plans to use sources optimum.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Definition and methodology of operations research, applications of operations research
2 Introduction to linear programming, the art of linear modeling, examples of linear decision models
3 Graphical solution of linear decision programming, finding feasible region
4 Special cases in the solution of linear decision programming, sensitivity analysis in graphic
5 Simplex algorithm, canonical and standard, steps of the simplex algorithm
6 Big M method
7 Two-Pase Simplex Method
8 Special cases in the solution of simplex algorithm
9 Duality, to write the dual model, economic interpretation
10 Dual simplex method
11 Sensitivity analysis in linear programming, sensitivity analysis for parameters
12 Sensitivity analysis according to structural changes
13 Solution methods of transportation problems
14 Solution methods of assignment problems
15 Adjusted simplex algorithm

Recomended or Required Reading

Textbook(s):
1. W. L. Winston, Operations Research-Applications and Algoritms, Duxbury Pres, 1994.
2. H. Taha, Operations Research, Prentice Hall Int. Inc., 2003.
3. F. S. Hillier & G. J. Lieberman, Introduction to Operations Research, McGraw Hill, 1995.
Supplementary Book(s):
1. I. Kara, Doğrusal Programlama, Bilim Teknik Yayınevi, 2000.

Planned Learning Activities and Teaching Methods

Problem analysis, design and application, presentation/lecturing and interactive discussion.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE* 0.25 + ASG* 0.25 + FIN* 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.25 + ASG* 0.25 + RST* 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homeworks, projects and exams.

Language of Instruction

Turkish

Course Policies and Rules

Attendance is an essential requirement of this course and is the responsibility of the student. Students are expected to attend all lecture and recitation hours. Attendance must be at least 70% for the lectures.

Contact Details for the Lecturer(s)

Dokuz Eylül University, Faculty of Science, Department of Statistics
e-mail: cengiz.celikoglu@deu.edu.tr
Tel: 0232 301 85 50

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 5 5
Preparation for final exam 1 10 10
Preparing assignments 1 22 22
Preparing presentations 1 5 5
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 100

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16
LO.155
LO.24454
LO.355
LO.444
LO.555
LO.655