ISE 3200
Transcript Abbreviation:
Opt Ent Sys
Course Description:
Introduction to formulation, solution and analysis of continuous and discrete linear models to optimize the design of production and service systems and other engineering applications.
Course Levels:
Undergraduate (1000-5000 level)
Designation:
Required
General Education Course
(N/A)
Cross-Listings
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours:
3.00
Select if Repeatable:
Off
Maximum Repeatable Credits:
3.00
Total Completions Allowed
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: Math 2568 or 2174, and CSE 1222 or 1223 or 1224 or Engr 1281.01H or 1281.02H, and enrollment in ISE or Engineering Physics major. Additional prereq for students enrolled in ISE major: CSE 2112. Additional prereq or co-req for students enrolled in ISE major: ISE 2400.
Electronically Enforced:
No
Exclusions
(N/A)
Course Goals / Objectives:
Model problems with linear objective and constraints, and discrete and continuous decision variables
Use simplex algorithm to solve linear programs
Understand duality and conduct sensitivity analysis
Model and solve network flow problems
Use branch-and-bound algorithm to solve mixed-integer linear programs
Use modeling and optimization software packages to model and solve linear and mixed-integer programs
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC | LAB | LAB Inst |
|---|---|---|---|---|
| Linear Programming Models | 9.0 | 0.0 | 0.0 | 0 |
| Linear Programming Solution Methods | 7.5 | 0.0 | 0.0 | 0 |
| Duality and Sensitivity Analysis | 6.0 | 0.0 | 0.0 | 0 |
| Network Flow Model and Methods | 4.5 | 0.0 | 0.0 | 0 |
| Integer Programming Models | 4.5 | 0.0 | 0.0 | 0 |
| Integer Programming Solution Methods | 3.0 | 0.0 | 0.0 | 0 |
| Software | 4.5 | 0.0 | 0.0 | 0 |
| Total | 39 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Lab
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Homeworks / Projects | 30% |
| Midterms / Quizzes | 40% |
| Final Exam | 30% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| Introduction to Mathematical Programming: Applications and Algorithms | Wayne L. Winston and Munirpallam Venkataramanan |
ABET-CAC Criterion 3 Outcomes
(N/A)
ABET-ETAC Criterion 3 Outcomes
(N/A)
ABET-EAC Criterion 3 Outcomes
(N/A)
Embedded Literacies Info
(N/A)
Attachments
(N/A)
Additional Notes or Comments
(N/A)