The essence of management is to make choices that make optimal use of scarce resources. This course covers how to apply linear programming to complex systems to make better decisions – decisions that increase revenue, decrease costs, or improve efficiency of operations. Students will explore the role of mathematical models in decision-making and how to formulate basic linear programming models where multiple decisions need to be made while simultaneously satisfying multiple conditions or constraints.
Optimization with Linear Programming
This course will teach you the use of mathematical models for managerial decision making and covers how to formulate linear programming models where multiple decisions need made while satisfying a number of conditions or constraints.
This course will teach you the use of mathematical models for managerial decision making and covers how to formulate linear programming models where multiple decisions need to be made while satisfying a number of conditions or constraints.
After completing this course students will be able to formulate linear programming models and describe the types of decisions that lend themselves to linear programming solutions. You will learn how to use spreadsheet software to implement and solve linear programming problems. You will also cover how to use sensitivity analysis and shadow prices to gain additional insights from linear programming results.
- Describe what types of decisions are amenable to linear programming solutions
- Formulate a linear programming model, and represent it graphically
- Solve the LP model with spreadsheet-based software
- Use LP models for various decisions: make or buy, where to invest,
- Use sensitivity analysis and shadow prices to gain additional information from the LP solution
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.
- The role of models in decisions
- Sources of bias & error in human decision making
- Good decisions vs. good outcomes
Linear Programming Models
- Formulating linear programming models
- Graphical representations
- Solving LP models in spreadsheets
Domain Specific Illustrations
- Make or buy
- Role of sensitivity analysis in the larger decision context
- Shadow prices
- Alternate solutions
- Robust Optimization
- Simplex Method
Jul 17, 2020 to Aug 14, 2020
No classes scheduled at this time.
No classes scheduled at this time.
You will need to have some facility with spreadsheet operations prior to starting this course.
There are no prerequisites for this course.
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Class Start Dates: Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021
Class Start Dates: Sep 25, 2020, Sep 24, 2021
Class Start Dates: May 1, 2020, Nov 13, 2020
Additional Course Information
Organization of Course
This course takes place online 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.
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.
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
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.
In addition to assigned readings, this course also has supplemental readings available online.
Spreadsheet Modeling & Decision Analysis, eighth edition by Cliff Ragsdale, which can be ordered from the publisher via the previous link. This text is also used in Integer & Nonlinear Programming and Network Flowand Risk Simulation and Queueing. Note: We do not recommend using the Kindle version of this book.
Please order a copy of your course textbook prior to course start date.
The course uses Analytic Solver Platform for Education software by Frontline systems. Analytic Solver Platform for Education is an 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. If you do not have such a license, a license is also available for course registrants through Statistics.com. Please do not install the regular public trial copy of the software on your own; when the course starts we will provide you with the complete installation instructions to obtain the appropriate copy of the software.
Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?”
Course Fee & Information
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
Contact us to get information on group rates.
Academic affiliation? In most courses you are eligible for a discount at checkout.
New to Statistics.com? Click here for a special introductory discount code.
Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.
Options for Credit and Recognition
This course is eligible for the following credit and recognition options:
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the the upper division baccalaureate degree, 3 semester hours in data mining, statistics, or computer science. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.
There is no supplemental content for this course.
There is no additional information for this course.
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