Integer and Nonlinear Programming and Network Flow
This course will teach you a number of advanced topics in optimization: how to formulate and solve network flow problems; how to model and solve optimization problems; how to deal with multiple objectives in optimization problems, and techniques for handling optimization problems.
Overview
Many business problems involve flows through a network – transportation, stages of an industrial process, routing of data. Students taking this course learn 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). Students also learn how to solve Integer Programming (IP) problems and Nonlinear Programming (NLP) problems. Spreadsheet-based software is used to specify and implement models.
- Intermediate
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
Students who complete this class are 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 & 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
Who Should Take This Course
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.
Our Instructors
Dr. Cliff Ragsdale
Course Syllabus
Week 1
Network Flow Problems
- Characteristics (nodes, arcs, decision variables)
- The objective function & constraints
- Modeling in a spreadsheet
Week 2
Integer Linear Programming
- Integrality condition, relaxation
- Rounding
- Stopping rules
- Binary variables
- Implementing/solving the model
- Branch & bound
Week 3
Multiple Goals
- Soft/hard constraints
- Defining the objective
- Analysis/solution
- Tradeoffs & goal revision
- Multiple objective linear programming (MOLP)
- Minimax
Week 4
Nonlinear Programming (NLP)
- Generalized reduced gradient (GRG) overview
- Local vs. Global optimality
- Economic Order Quantity (EOQ) problem
- Location problem
- Evolutionary Optimization
Class Dates
2024
Instructors: Dr. Cliff Ragsdale
2025
Instructors: Dr. Cliff Ragsdale
Prerequisites
Optimization with Linear Programming
- Skill: Intermediate
- Credit Options: ACE, CAP, CEU
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Register For This Course
Integer and Nonlinear Programming and Network Flow
Additional Information
Homework
Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.
Course Text
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 our courses, Introduction to Optimization and Risk Simulation and Queueing. We do not recommend using the Kindle version of this book.
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 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.
Options for Credit and Recognition
ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate degree, 3 semester hours in operation research, computer programming, statistics, or computer information systems. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
Supplemental Information
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