Introduction to Optimization

taught by Cliff Ragsdale

Brief Description:

The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems.

Instructor(s):
Level: Introductory

Who Should Take This Course:

Business analysts with responsibility for specifying, creating, deploying or interpreting quantitative decision models.  Users of linear programming software who need to attain a more solid grounding in the subject.

Dates:
August 24, 2012 to September 21, 2012
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
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Introduction to Optimization

taught by Cliff Ragsdale

Aim of Course:

Scarcity is a dominant feature of the economic landscape - time, labor and other inputs into business processes.  The essence of management is to make choices that make optimal use of scarce resources. Students in this course will learn how to apply linear programming to complex systems to make better decisions - decisions that increase revenue, decrease costs, or improve efficiency of operation.   The course introduces the role of mathematical models in decision-making, then covers how to formulate basic linear programming models for decision problems where multiple decision need to be made in the best possible way, while simultaneously satisfying a number of logical conditions (or constraints).  Students will use spreadsheet software to implement and solve these linear programming problems.

Prerequisite(s):
You will need to have some facility with spreadsheet operations prior to starting this course.

Course Program:

SESSION 1: Introduction

• The role of models in decisions
• Sources of bias & error in human decision making
• Good decisions vs. good outcomes

SESSION 2: Linear Programming Models

• Formulating linear programming models
• Graphical representations
• Solving LP models in spreadsheets

SESSION 3: Domain Specific Illustrations

• Make or buy
• Investment
• Transportation
• Blending

SESSION 4: Sensitivity Analysis

• Role of sensitivity analysis in the larger decision context
• Shadow prices
• Alternate solutions
• Robust Optimization
• Simplex Method

HOMEWORK:

Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

Organization of the Course:

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Credit:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

Spreadsheet Modeling & Decision Analysis, Sixth edition by Cliff Ragsdale, which can be ordered from the publisher here.  Please be aware that if you order the ebook or rent the text, you will also need to purchase the companion resources which will give you the access to the software.  This text is also used in Advanced Optimization and Risk Simulation and Queueing.

Note:  It is important to get the sixth edition of the text; earlier editions do not contain correct assignments, nor do they provide the needed access to the software.

Software:

The course uses Risk Solver Platform for Education software by Frontline systems.  Risk Solver Platform for Education is a new add-in for Excel that performs risk analysis, simulation, optimization, decision trees and other analytical methods.  With the purchase or rental of the book, you will have a course code that will enable you to download and install the software for 140 days.

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Introduction to Optimization

taught by Cliff Ragsdale

Instructor(s):
Dates:
August 24, 2012 to September 21, 2012
Course Fee: $499
Academic Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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