MgS 8140  Management Science
Syllabus
Spring, 2010 Dr. Whalen   Click here for schedule
  email       fax 1-626-605-2586

Prerequisite: Advanced Spreadsheet Skills (CSP 1, 3, 4, 7)
 
Required Texts:  Linear Programming Fundamentals. Whalen & Churchill, available online: see links from schedule
2  The entire class web structure accessable from the schedule, is also essential reading for the course.
3.  Course pack available at Study.net

Detailed Course Description

The course begins by considering a very simple linear resource allocation problem to introduce linear programming, dimensional analysis, and sensitivity analysis in a simple setting.  Progressively more complex resource allocation problems illustrate slack and surplus variables, allocating financial resources and formulation issues

Personnel shift coverage problems and assignment problems are important in themselves and also provide an introduction to the use of matrices in linear programming.  Next come multi-period inventory, single & multi-period Finance, and production, inventory,  and finance all together.

Linear transportation models lead into a section on capacitated transshipment problems. These are key issues in supply chain management.  The problem of warehouse location in two-stage supply chain optimization provides an introduction to integer programming.

The next section considers blending problems, especially problems in which there is some flexibility in the ingredients of two or more products.

Quadratic programming is introduced in a context of financial portfolios , and a synthesis of quadratic and integer programming is presented in the context of price determination.  General nonlinear programming is introduces in the context of optimal order quantity (which is mathematically the same as optimal production runs).

The course concludes with a unit on goal programming to balance conflicting objectives.  fuzzy linear programming is briefly introduced in the context of goal programming.
 

Learning Outcomes/Course Objectives

At the conclusion of this course, the student should be able to:
  • Determine whether a particular business case or situation calls for an optimization model
  • Choose an appropriate linear, nonlinear, dynamic, or fuzzy optimization technique, and
  • Implement an optimization model to inform the business decision making process.
  •  

    Methods of Instruction

    Instruction is by lecture and discussion, with some in-class exercises.  Homework projects are also integral to the instruction,  and students are strongly encouraged to use the instructor as a resource throughout these projects via email and other methods.

    Grading Criteria

    Grading will be based on four  components, weighted equally:
    *  Homework Assignments
    *  In Cass Midterm
    *  Comprehensive Take Home Final Exam
    *  Project

    A grade of A will not normally be given to students whose average is below the class mean or median

    Homework Assignments:
    Homework assignments are integral to the instruction,  and students are strongly encouraged to use the instructor as a resource throughout these projects via email and other methods.  
    If homework is turned in on time, you get a "second chance" to re-do it after getting it back; the final grade for the homework will be the average of the two tries or A-, whichever is lower.  (Thus, if you get A- the first time there's no incentive to re-do.)  Late homework is assessed a one-step penalty per class period late  (for example, A becomes A-, A- becomes B+, and so on), and there is no second chance on late homework.
    I welcome specific questions about the homework; email your questions to 8140 [at] whalen3 [dot] org
    "Tell me how to do this assignment so I don't have to think for myself" or "Here's my answer; grade it ahead of time so I can get an extra free re-do if it's wrong" do not qualify as "specific questions."

    You mist work individually on the homework.   Copying another's work, knowingly or negligently allowing another to copy yours, or collaborating on a rough draft you both copy from will all result in a grade of F for the entire course.  This includes computer work.


    In-Class Midterm:
    The midterm is multiple-choice, based on interpretation of Excel printouts (Including sensitivity analysis)

    Comprehensive Take Home Final Exam:
    Some exam questions will involve setting up a problem, others will involve interpreting Excel printouts of the results.
    You mist work individually on the final.   Copying another's work, knowingly allowing another to copy yours, or collaborating on a rough draft you both copy from will all result in a grade of F for the entire course.  This includes computer work.

    Project:   Click here for the project


    Course Outline:  Click here for schedule