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INLPUndergraduate courses

Integer and Nonlinear Programming and Network Flow

Advanced optimization — network flow problems, integer and nonlinear programming, and what to do when a decision has more than one objective.

  • Intermediate
  • 4 weeks
  • Approx. 15 hours per week
  • 3 semester hours

About this course

Many business problems involve flows through a network — transportation, stages of an industrial process, routing of data. This course teaches you to specify and implement optimization models that solve network problems: what is the shortest path through a network, what is the least cost way to route material through a network with multiple supply nodes and multiple demand nodes. It goes on to Integer Programming (IP) problems and Nonlinear Programming (NLP) problems, and to decisions that carry several goals at once. Spreadsheet-based software is used to specify and implement the models.

Who this course is for

Business analysts with responsibility for specifying, creating, deploying or interpreting quantitative decision models. Users of optimization software who need to attain a more solid grounding in network optimization, integer programming, non-convex optimization and multi-criteria optimization.

What you will learn

8 outcomes

By the end of this course, you will be able to:

  • Describe the characteristics of a network flow problem
  • Specify an objective function and constraints for a network problem, and model it with software
  • Solve the integer programming problem with software
  • Appropriately use rounding and stopping rules, and branch and bound
  • Describe the scenario in which an integer programming method is used
  • Specify an integer programming model
  • Accommodate multiple goals in the analysis
  • Specify a nonlinear programming model

Week by week

4-Week curriculum overview

This curriculum is identical across all start dates. Expand a week to explore the topics covered.

Weeks
4
Your week
Approx. 15 hours
Level
Intermediate
Network flow problemsWeek 1
  • Characteristics — nodes, arcs, decision variables
  • The objective function and constraints
  • Modeling in a spreadsheet
Integer linear programmingWeek 2
  • Integrality condition, relaxation
  • Rounding
  • Stopping rules
  • Binary variables
  • Implementing and solving the model
  • Branch and bound
Multiple goalsWeek 3
  • Soft and hard constraints
  • Defining the objective
  • Analysis and solution
  • Tradeoffs and goal revision
  • Multiple objective linear programming (MOLP)
  • Minimax
Nonlinear programming (NLP)Week 4
  • Generalized reduced gradient (GRG) overview
  • Local versus global optimality
  • Economic Order Quantity (EOQ) problem
  • Location problem
  • Evolutionary optimization

Instructors

Expert-Led Guidance

Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments.

  • Dr. Cliff Ragsdale

    Cliff T. Ragsdale is Bank of America Professor of Business Information Technology at Virginia Tech. His primary research interests involve applications of quantitative modeling techniques to managerial decision making problems using microcomputers. Dr. Ragsdale has served as a consultant for a variety of organizations including General Mills, The World Bank, Frontline Systems, and Dominion Energy. His research has been published in Decision Sciences, Naval Research Logistics, Operations Research Letters, Computers and Operations Research, OMEGA, Personal Financial Planning, Financial Services Review, Decision Support Systems, and a number of other scholarly journals. He is a Fellow of Decision Sciences Institute and a member of INFORMS. He has also served as the faculty advisor for the Virginia Tech student chapter of APICS and on the Board of Directors for the Southwest Chapter of APICS.

Before you start

What you need to know first

Optimization — Linear Programming

Course Format & Schedule

This is a 4-week, 100% online, asynchronous course.

  • No mandatory live sessions: Log in and complete your work at times that fit your schedule.
  • Weekly Releases: At the start of each week, you will receive new lecture materials and answer keys for the previous week's exercises.
  • Interactive Community: Work through exercises, submit assignments, and engage with your instructor and peers via a private discussion board.
Homework

Short-answer questions testing the concepts, and guided data analysis problems using software.

Texts

Spreadsheet Modeling & Decision Analysis, ninth edition, by Cliff Ragsdale, ordered from the publisher. The same text carries you through Optimization — Linear Programming and Risk Simulation and Queuing, so one copy covers all three. Also available at Amazon here. The Kindle version is not recommended.

Software

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 LearnStatistics. 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.

FAQ

Do I have to take Optimization — Linear Programming first?This course

Yes, or you need the equivalent from elsewhere. Week one starts by writing an objective function and constraints for a network problem and modeling it in a spreadsheet, which assumes you can already formulate and solve an LP.

Can I use the text and software I already have from Optimization — Linear Programming?This course

Yes. Both courses use Ragsdale's Spreadsheet Modeling & Decision Analysis and the Analytic Solver add-in for Excel, so one copy of each covers you.

Is there a money-back or satisfaction guarantee?Every course

We handle cancellation and refund requests on an individual basis. If a course is not meeting your expectations or your circumstances change, please reach out to our team (support@learnstatistics.org) so we can work with you on a solution.

Can I transfer to a later start date or withdraw after the course begins?Every course

Yes. If you need to defer your enrollment to a future start date, withdraw mid-course, or transfer your seat to a colleague, please contact us directly. We address these requests flexibly on a case-by-case basis.

Who teaches the course?Every course

Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments.

Something not answered here? Ask us before you book — and the terms set out what a purchase covers.

Credit, and where it counts

This course carries a verified figure of 3 semester hours. A credit recommendation from the American Council on Education says what a course is worth; the institution receiving it decides whether to award it.

Anyone can take this subject: there is no application, and you do not have to be studying at a university. It also counts toward a degree at Thomas Edison State University, which decides what to award for it. The full position — including the limits each university publishes is on its own page, and worth reading before you buy.