IE 471

Course ID:

Course Code & Number

IE 471

Course Title

Computational Tools for Industrial Engin

Level

BS

Credit Hours/ ECTS Credits

(2+2+0) 3 TEDU Credits, 5 ECTS Credits

Year of Study:

Senior

Semester:

Fall

Type of Course:

Elective

Mode of Delivery:

Face-to-face

Language of Instruction:

English

Pre-requisite / Co-requisite::

Catalog Description

Introduction to computational tools. Algebraic modeling of selected Integer/Linear programs with GAMS. Mathematical and statistical modeling with Python and R. Solving LP, MIP and NLP models with Gurobi. Implementing selected optimization algorithms in Python and/or R. Shaping and analyzing data. Analyzing and visualizing data using Excel, R. Preliminary Statistical Analysis with R.

Course Objectives

The main objective of this course is to introduce useful computational tools for industrial engineers with emphasis on algebraic modelling, implementation of algebraic in different computer languages/environments, and developing skills
to automate statistical analysis and visualization of data.

Software Usage

Excel, MATLAB, Octave, R, Python, GAMS, GUROBI

Course Learning Outcomes

Upon successful completion of this course, a student will be able to
1. Model and implement algebraic formulations in GAMS, AMPL and Python/Gurobi,
2. Use various software and computer languages for solving operations research problems,
3. Develop selected LP/IP/NLP models and implement/solve these models using open source and commercial
solvers such as GLPK, Excel Solver, CPLEX and Gurobi.
4. Conduct data analysis, statistical analysis and data visualization using Excel, MATLAB, Octave, R, Python.

Learning Activities and Teaching Methods:

Telling/Explaining Discussion/Debate Questioning Reading Demonstrating Problem Solving Web Searching

Assessment Methods and Criteria:

Test / Exam Quiz Lab Assignment Case Studies / Homework

Assessment Methods and Criteria Others:

Design Content

Recommended Reading

Required Reading

Grading

Learning Activities and Teaching Methods Others:

Course Coordinator:

Student Workload:

Workload	Hrs
Course Readings	30
Observation	6
Exams/Quizzes	82

Course & Program Learning Outcome Matching: