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Graduate Course Proposal Form Submission Detail - ESI6447

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Current Status: Approved, Permanent Archive - 2011-07-17
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: COEN app 5/10/11; to GC 5/10/11; why Is title variable? Emailed 6/28/11. cleared 6/29/11; GC approved 7/5/11. To USF Syst 7/5/11; to SCNS 7/13/11. Appd Eff 8/1/11


  1. Department and Contact Information

    Tracking Number Date & Time Submitted
    2471 2011-02-17
     
    Department College Budget Account Number
    Industrial and Management Systems Engineering EN
     
    Contact Person Phone Email
    Bo Zeng 9745588 bzeng@usf.edu

  2. Course Information

    Prefix Number Full Title
    ESI 6447 Large-scale and Computational Optimization

    Is the course title variable? N
    Is a permit required for registration? Y
    Are the credit hours variable? N
    Is this course repeatable?
    If repeatable, how many times? 0

    Credit Hours Section Type Grading Option
    3 C - Class Lecture (Primarily) R - Regular
     
    Abbreviated Title (30 characters maximum)
    Large-scale Optimization
     
    Course Online? Percentage Online
    C - Face-to-face (0% online) 0

    Prerequisites

    ESI 6491

    Corequisites

    Course Description

    Efficient algorithm development for large-scale and computationally intensive optimization problems. Specific topics include Lagrangian relaxation, Benders' decomposition, column generation and primal-dual approximation algorithms.


  3. Justification

    A. Please briefly explain why it is necessary and/or desirable to add this course.

    Replacing Selected Topics with Permanent number; already listed in program

    B. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service?

    It was started to taught in Spring 2010. 11 doctoral students were enrolled in this course. It is anticipated that the demand will be kept or be higher given the current national trend in "Operations Research", one of the core area in Industrial Engineering, as well as the computational demand in bio-informatics, power systems and transportation systems.

    C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?

    Yes, 1 time

    D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)


  4. Other Course Information

    A. Objectives

    • Developing analytical mathematical programming models for designing and operating large-scale systems, such as those from logistic, transportation, power, telecommunication systems as well as portfolio optimization.

    • Understand the computational complexity theory and concepts of algorithm design

    • Master typical algorithms for those challenging problems, such as various decomposition algorithms, Lagrangian Relaxation method, and several approximation algorithms.

    • Be able to apply methods and skills to solve practical system design and operation issues using popular software and commercial solvers

    B. Learning Outcomes

    • Strong modeling ability for practical systems

    • Efficient solution algorithm development for typical models

    • Insights into the computational complexity and approximation strategies

    C. Major Topics

    • Lagrangian relaxation/decomposition

    • Bender’s decomposition and L-shape method in stochastic programming

    • Dantzig-Wolfe decomposition/ column generation

    • Primal-dual algorithm

    • Branch-and-bound method

    D. Textbooks

    Large Scale Linear and Integer Optimization-by R. Kipp Martin

    Integer Programming- by L. Wolsey

    E. Course Readings, Online Resources, and Other Purchases

    F. Student Expectations/Requirements and Grading Policy

    3-4 homework assignments and one course project.

    G. Assignments, Exams and Tests

    3-4 homework assignments and one course project.

    H. Attendance Policy

    Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,

    http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

    I. Policy on Make-up Work

    J. Program This Course Supports

    Department of Industrial and Management Systems Engineering


  5. Course Concurrence Information

    1, Computer Science and Engineering

    2, Electric Engineering

    3, Civil and Environmental Engineering

    4, Chemical Engineering



- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.