Department of Computer Engineering

CE 485 | Course Introduction and Application Information

Course Name

Linear and Integer Programming

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
CE 485	FALL	3	0	3	8

Prerequisites	None
Course Language	English
Course Type	ELECTIVE_COURSE
Course Level	First Cycle
Mode of Delivery	Face-To-Face
Teaching Methods and Techniques of the Course	Problem Solving Lecture / Presentation
National Occupational Classification Code	-
Course Coordinator	Prof. Dr. Cem Evrendilek
Course Lecturer(s)	-
Assistant(s)	-

Course Objectives

The primary objective is to develop both an understanding of the formulation techniques, and the algorithms used to solve the class of optimization problems that lend themselves to linear and integer linear programming.

Learning Outcomes

The students who succeeded in this course;

Name	Description	PC Sub	* Contribution Level
Name	Description	PC Sub	1	2	3	4	5
LO1	will be able to create LP formulations to appropriate problems.						X
LO2	will be able to apply simplex and dual simplex methods.						X
LO3	will be able to express the run-time complexity of various algorithms for solving LP problems.						X
LO4	will be able to formulate Integer LP (ILP) formulations for various combinatorial problems.						X
LO5	will be able to employ techniques for relaxation of the ILP models to the corresponding LP formulations.						X

Course Description

LP Standard Form, Extreme Points and Basic Solutions, Rudimentary Simplex Algorithm, Interior Point Strategies for LP, Formulating Duals, Primal-to-Dual Relationships, LP-Based Branch and Bound, and Rounding.

Related Sustainable Development Goals

Course Category	Core Courses
	Major Area Courses	X
	Supportive Courses
	Media and Managment Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials	Learning Outcome
1	Nature of Linear Programs	Section 2.4	LO1
2	Formulation of Classic LP Model Types	Chapter 4	LO1
3	LP Standard Form, Extreme Points and Basic Solutions, Rudimentary Simplex Algorithm	Section 5.1, Section 5.2, Section 5.3	LO2
4	Two Phase Simplex, Degeneracy, Cycling and Finiteness of Simplex	Section 5.5, Sections 5.6, Section 5.7	LO2
5	Revised Simplex, Lower- and Upper-Bounded Simplex	Section 5.8, Section 5.9	LO2
6	Interior Point Strategies for LP, Affine Scaling of Solutions, Affine Scaling Search	Section 6.1, Section 6.2, Section 6.3	LO3
7	Log Barrier Methods for LP, Primal-Dual Search	Section 6.4, Section 6.5	LO3
8	Midterm		-
9	Activities vs. Resources, Qualititative Sensitivity	Sections 7.1-7.2	LO3
10	Quantitative Sensitivity and Duality, Formulating Duals, Primal-to-Dual Relationships	Section 7.3, Section 7.4, Section 7.5	LO3
11	Solving by Total Enumeration, Elementary Relaxations, Strengthening LP Relaxations	Section 12.1, Section 12.2, Section 12.3	LO5
12	LP-Based Branch and Bound	Section 12.4	LO4
13	Rounding, Parent Bounds, Enumeration Sequences and Stopping Early in Branch and Bound	Section 12.5	LO4
14	Improving Heuristics for Discrete Optimization, Tabu, Simulated Annealing, Genetic Algorithms, Constructive Heuristics for Discrete Optimization	Section 12.6, Section 12.7, Section 12.8	LO4
15	Semester Review		-
16	Final Exam		-

Course Notes/Textbooks	Optimization in Operations Research Ronald L. Rardin Prentice Hall ISBN-10: 0023984155 • ISBN-13: 9780023984150 1998.
Suggested Readings/Materials	-

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO1	LO2	LO3	LO4	LO5
Homework / Assignments	1	30	X	X	X	X	X
Midterm	1	30	X	X	X
Final Exam	1	40			X	X	X
Total	3	100

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Participation	-	-	-
Theoretical Course Hours	16	3	48
Laboratory / Application Hours	-	-	-
Study Hours Out of Class	14	6	84
Field Work	-	-	-
Quizzes / Studio Critiques	-	-	-
Portfolio	-	-	-
Homework / Assignments	6	10	60
Presentation / Jury	-	-	-
Project	-	-	-
Seminar / Workshop	-	-	-
Oral Exams	-	-	-
Midterms	1	16	16
Final Exam	1	32	32
		Total	240

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
			1	2	3	4	5
No program competency data found.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

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