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Operations Research Course Specifications
Program(s) on which the course is given
Computing, Computer Systems
:
Computer Science, Information Systems, Scientific
Major or Minor element of programs
:
Department offering the program
Computing, Computer Systems
:
Computer Science, Information Systems, Scientific
Department offering the course
:
Scientific Computing
Academic year / Level
:
second Year./B.Sc.
Date of specification approval
:
all majors
23/3/2009
A. Basic Information
Title: Operations Research
Code: SCC 231
Lecture:
Tutorial: 2 hrs/week
3 hrs/week
Credit Hours: ---
Practical: ---
Total: 5 hrs/week
B. Professional Information
1. Overall Aims of Course:
The aim of the course is to introduce the students to the fundamental methods used in
operations research. Topics covered will include linear programming, network flows,
dynamic programming, and transportation programming. The course will also discuss the
underlying theory, but the emphasis will be on modeling and applications in various
settings.
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‫كلية الحاسبات و المعلومات‬
2. Intended Learning Outcomes of Course (ILOs):
a. Knowledge and Understanding:
a1- Knowledge of informal and formal modeling skills.
a2- Knowledge of the different models and algorithms used in operations research
a3- Understand and appreciate the capabilities and limitations of deterministic models in
operations research.
b. Intellectual Skills:
b1- Build, analyze, and reason logically with mathematical models;
b2- Propose and integrate with large-scale models;
b3- Integrate skills to design and analyze algorithms, and to distinguish good
algorithms from not-so good ones
c.
Professional and Practical Skills:
c1- Inject knowledge of the varied applications of operations research
c2- Problem solving skills using appropriate modeling techniques
d. General and Transferable Skills:
d1- Presenting knowledge of various modeling methods in different settings and
applications and present them
e. Attitude:
e1. Relationship Emphasis a successful with other students.
e2. Learn how to make relation with other, and the limit of this relation.
e3. A knowledge and respect of ethics and ethical standards in relation to a major
area of study.
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‫كلية الحاسبات و المعلومات‬
3. Contents:
No. of
hours
Lecture
Tutorial/
Practical
Modeling; Introduction to Optimization
ModelsLinear programming: Formulations
and graphical solution.. (Part I)
5
3
2
Modeling; Introduction to Optimization Models Linear programming:
Formulations and graphical solution.. (Part II)
5
3
2
Modeling; Introduction to Optimization Models Linear programming:
Formulations and graphical solution.. (Part III)
5
3
2
Algebraic solution: the simplex method and dual-simplex
method. Sensitivity analysis. Transportation and assignment
problems(Part I)
5
3
2
Algebraic solution: the simplex method and dual-simplex
method. Sensitivity analysis. Transportation and assignment
problems(Part II)
5
3
2
Algebraic solution: the simplex method and dual-simplex
method. Sensitivity analysis. Transportation and assignment
problems(Part III)
5
3
2
Network models: transportation, assignment, matching(Part I)
5
3
2
Network models: transportation, assignment, matching(Part II)
5
3
2
Integer programming: cutting-plane algorithms, branch and
bound method. (Part I)
5
3
2
Integer programming: cutting-plane algorithms, branch and
bound method. (Part II)
5
3
2
Dynamic programming: Examples of the dynamic programming.
Models and computations, solution of linear programs by
dynamic programs.(Part I)
5
3
2
Topic
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‫كلية الحاسبات و المعلومات‬
Dynamic programming: Examples of the dynamic programming.
Models and computations, solution of linear programs by
dynamic programs.(Part II)
5
3
2
Project scheduling by PERT-CPM. Methods(Part I)
5
3
2
Project scheduling by PERT-CPM. Methods(Part II)
5
3
2
4. T
eaching and Learning Methods:
4.1- Lectures, directed reading and Web-based information sources.
4.2- Supervised practical sessions, in-course formative and summative assignments.
5. Student Assessment Methods:
5.1- Assignments
to assess
progress on students’ learning,
effectiveness of course materials, and
approaches to instruction
5.2- Mid-Term exam
to assess
level of knowledge acquisition and
concepts understanding that can be
used as a feedback for enhancing the
learning process
5.3- Oral exam
to assess
communication of technical
information that demonstrate
scientific understanding
5.4- Semester Final exam
to assess
level of mastery of the concepts,
algorithms, and problem solving
techniques learned in the course
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Assessment Schedule
Assessment 1
Midterm
Week 7
Assessment 2
Assignments
Weekly
Assessment 3
quizzes
Week 3, 5
Assessment 4
Oral Exam
Week 15
Assessment 5
End of Term final Exam
Week 16
Weighting of Assessments:
Semester Work
15 %
Final-Term Examination
75 %
Oral Examination
10 %
Practical Examination
0%
Other types of assessment
0%
latoT
100 %
Formative assessments

Assignments
6. List of references:
6.1- Essential Books (Text Books)

Hamdy A. Tahad, Operations Research 2007.
7. Facilities Required for Teaching and Learning
Lecture Hall, Exercises Hall, and Audiovisual equipments
Course Coordinator: Prof.Dr. EL-Sayed Badr
Signature: (
Head of Department: Prof. Dr. MOHMED SALAH
Signature: (
Date: 23/1/2014
)
)